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3 Steps to Proactively Address Board-Level Security Concerns

By E.G. Nadhan, HP

Last month, I shared the discussions that ensued in a Tweet Jam conducted by The Open Group on Big Data and Security where the key takeaway was: Protecting Data is Good.  Protecting Information generated from Big Data is priceless.  Security concerns around Big Data continue to the extent that it has become a Board-level concern as explained in this article in ComputerWorldUK.  Board-level concerns must be addressed proactively by enterprises.  To do so, enterprises must provide the business justification for such proactive steps needed to address such board-level concerns.

Nadhan blog image

At The Open Group Conference in Sydney in April, the session on “Which information risks are shaping our lives?” by Stephen Singam, Chief Technology Officer, HP Enterprise Security Services, Australia provides great insight on this topic.  In this session, Singam analyzes the current and emerging information risks while recommending a proactive approach to address them head-on with adversary-centric solutions.

The 3 steps that enterprises must take to proactively address security concerns are below:

Computing the cost of cyber-crime

The HP Ponemon 2012 Cost of Cyber Crime Study revealed that cyber attacks have more than doubled in a three year period with the financial impact increasing by nearly 40 percent. Here are the key takeaways from this research:

  • Cyber-crimes continue to be costly. The average annualized cost of cyber-crime for 56 organizations is $8.9 million per year, with a range of $1.4 million to $46 million.
  • Cyber attacks have become common occurrences. Companies experienced 102 successful attacks per week and 1.8 successful attacks per company per week in 2012.
  • The most costly cyber-crimes are those caused by denial of service, malicious insiders and web-based attacks.

When computing the cost of cyber-crime, enterprises must address direct, indirect and opportunity costs that result from the loss or theft of information, disruption to business operations, revenue loss and destruction of property, plant and equipment. The following phases of combating cyber-crime must also be factored in to comprehensively determine the total cost:

  1. Detection of patterns of behavior indicating an impending attack through sustained monitoring of the enabling infrastructure
  2. Investigation of the security violation upon occurrence to determine the underlying root cause and take appropriate remedial measures
  3. Incident response to address the immediate situation at hand, communicate the incidence of the attack raise all applicable alerts
  4. Containment of the attack by controlling its proliferation across the enterprise
  5. Recovery from the damages incurred as a result of the attack to ensure ongoing business operations based upon the business continuity plans in place

Identifying proactive steps that can be taken to address cyber-crime

  1. “Better get security right,” says HP Security Strategist Mary Ann Mezzapelle in her keynote on Big Data and Security at The Open Group Conference in Newport Beach. Asserting that proactive risk management is the most effective approach, Mezzapelle challenged enterprises to proactively question the presence of shadow IT, data ownership, usage of security tools and standards while taking a comprehensive approach to security end-to-end within the enterprise.
  2. Art Gilliland suggested that learning from cyber criminals and understanding their methods in this ZDNet article since the very frameworks enterprises strive to comply with (such as ISO and PCI) set a low bar for security that adversaries capitalize on.
  3. Andy Ellis discussed managing risk with psychology instead of brute force in his keynote at the 2013 RSA Conference.
  4. At the same conference, in another keynote, world re-knowned game-designer and inventor of SuperBetter, Jane McGonigal suggested the application of the “collective intelligence” that gaming generates can combat security concerns.
  5. In this interview, Bruce Schneier, renowned security guru and author of several books including LIARS & Outliers, suggested “Bad guys are going to invent new stuff — whether we want them to or not.” Should we take a cue from Hollywood and consider the inception of OODA loop into the security hacker’s mind?

The Balancing Act.

Can enterprises afford to take such proactive steps? Or more importantly, can they afford not to?

Enterprises must define their risk management strategy and determine the proactive steps that are best in alignment with their business objectives and information security standards.  This will enable organizations to better assess the cost of execution for such measures.  While the actual cost is likely to vary by enterprise, inaction is not an acceptable alternative.  Like all other critical corporate initiatives, these proactive measures must receive the board-level attention they deserve.

Enterprises must balance the cost of executing such proactive measures against the potential cost of data loss and reputational harm. This will ensure that the right proactive measures are taken with executive support.

How about you?  Has your enterprise taken the steps to assess the cost of cybercrime?  Have you considered various proactive steps to combat cybercrime?  Share your thoughts with me in the comments section below.

NadhanHP Distinguished Technologist, E.G.Nadhan has over 25 years of experience in the IT industry across the complete spectrum of selling, delivering and managing enterprise level solutions for HP customers. He is the founding co-chair for The Open Group SOCCI project and is also the founding co-chair for the Open Group Cloud Computing Governance project. Twitter handle @NadhanAtHP.

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Join us for The Open Group Conference in Sydney – April 15-18

By The Open Group Conference Team

The Open Group is busy gearing up for the Sydney conference, which will take place on April 15-18, 2013. With over 2,000 Associate of Enterprise Architects (AEA) members in Australia, Sydney is an ideal setting for industry experts from around the world to gather and discuss the evolution of Enterprise Architecture and its role in transforming the enterprise. Be sure to register today!

The conference offers roughly 60 sessions on a varied of topics including:

  • Cloud infrastructure as an enabler of innovation in enterprises
  • Simplifying data integration in the government and defense sectors
  • Merger transformation with TOGAF® framework and ArchiMate® modeling language
  • Measuring and managing cybersecurity risks
  • Pragmatic IT road-mapping with ArchiMate modeling language
  • The value of Enterprise Architecture certification within a professional development framework

Plenary speakers will include:

  • Allen Brown, President & CEO, The Open Group
  • Peter Haviland, Chief Business Architect, with Martin Keywood, Partner, Ernst & Young
  • David David, EA Manager, Rio Tinto
  • Roger Venning, Chief IT Architect, NBN Co. Ltd
  • Craig Martin, COO & Chief Architect, Enterprise Architects
  • Chris Forde, VP Enterprise Architecture, The Open Group

The full conference agenda is available here. Tracks include:

  • Finance & Commerce
  • Government & Defense
  • Energy & Natural Resources

And topics of discussion include, but are not limited to:

  • Cloud
  • Business Transformation
  • Enterprise Architecture
  • Technology & Innovation
  • Data Integration/Information Sharing
  • Governance & Security
  • Architecture Reference Models
  • Strategic Planning
  • Distributed Services Architecture

Upcoming Conference Submission Deadlines

Would you like a chance to speak an Open Group conference? There are upcoming deadlines for speaker proposal submissions for upcoming conferences in Philadelphia and London. To submit a proposal to speak, click here.

Venue Industry Focus Submission Deadline
Philadelphia (July 15-17) Healthcare, Finance, Government & Defense April 5, 2013
London (October 21-23) Finance, Government, Healthcare July 8, 2013

 

The agenda for Philadelphia and London are filling up fast, so it is important for proposals to be submitted as early as possible. Proposals received after the deadline dates will still be considered, space permitting; if not, proposals may be carried over to a future conference. Priority will be given to proposals received by the deadline dates and to proposals that include an end-user organization, at least as a co-presenter.

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Beyond Big Data

By Chris Harding, The Open Group

The big bang that started The Open Group Conference in Newport Beach was, appropriately, a presentation related to astronomy. Chris Gerty gave a keynote on Big Data at NASA, where he is Deputy Program Manager of the Open Innovation Program. He told us how visualizing deep space and its celestial bodies created understanding and enabled new discoveries. Everyone who attended felt inspired to explore the universe of Big Data during the rest of the conference. And that exploration – as is often the case with successful space missions – left us wondering what lies beyond.

The Big Data Conference Plenary

The second presentation on that Monday morning brought us down from the stars to the nuts and bolts of engineering. Mechanical devices require regular maintenance to keep functioning. Processing the mass of data generated during their operation can improve safety and cut costs. For example, airlines can overhaul aircraft engines when it needs doing, rather than on a fixed schedule that has to be frequent enough to prevent damage under most conditions, but might still fail to anticipate failure in unusual circumstances. David Potter and Ron Schuldt lead two of The Open Group initiatives, Quantum Lifecycle management (QLM) and the Universal Data Element Framework (UDEF). They explained how a semantic approach to product lifecycle management can facilitate the big-data processing needed to achieve this aim.

Chris Gerty was then joined by Andras Szakal, vice-president and chief technology officer at IBM US Federal IMT, Robert Weisman, chief executive officer of Build The Vision, and Jim Hietala, vice-president of Security at The Open Group, in a panel session on Big Data that was moderated by Dana Gardner of Interarbor Solutions. As always, Dana facilitated a fascinating discussion. Key points made by the panelists included: the trend to monetize data; the need to ensure veracity and usefulness; the need for security and privacy; the expectation that data warehouse technology will exist and evolve in parallel with map/reduce “on-the-fly” analysis; the importance of meaningful presentation of the data; integration with cloud and mobile technology; and the new ways in which Big Data can be used to deliver business value.

More on Big Data

In the afternoons of Monday and Tuesday, and on most of Wednesday, the conference split into streams. These have presentations that are more technical than the plenary, going deeper into their subjects. It’s a pity that you can’t be in all the streams at once. (At one point I couldn’t be in any of them, as there was an important side meeting to discuss the UDEF, which is in one of the areas that I support as forum director). Fortunately, there were a few great stream presentations that I did manage to get to.

On the Monday afternoon, Tom Plunkett and Janet Mostow of Oracle presented a reference architecture that combined Hadoop and NoSQL with traditional RDBMS, streaming, and complex event processing, to enable Big Data analysis. One application that they described was to trace the relations between particular genes and cancer. This could have big benefits in disease prediction and treatment. Another was to predict the movements of protesters at a demonstration through analysis of communications on social media. The police could then concentrate their forces in the right place at the right time.

Jason Bloomberg, president of Zapthink – now part of Dovel – is always thought-provoking. His presentation featured the need for governance vitality to cope with ever changing tools to handle Big Data of ever increasing size, “crowdsourcing” to channel the efforts of many people into solving a problem, and business transformation that is continuous rather than a one-time step from “as is” to “to be.”

Later in the week, I moderated a discussion on Architecting for Big Data in the Cloud. We had a well-balanced panel made up of TJ Virdi of Boeing, Mark Skilton of Capgemini and Tom Plunkett of Oracle. They made some excellent points. Big Data analysis provides business value by enabling better understanding, leading to better decisions. The analysis is often an iterative process, with new questions emerging as answers are found. There is no single application that does this analysis and provides the visualization needed for understanding, but there are a number of products that can be used to assist. The role of the data scientist in formulating the questions and configuring the visualization is critical. Reference models for the technology are emerging but there are as yet no commonly-accepted standards.

The New Enterprise Platform

Jogging is a great way of taking exercise at conferences, and I was able to go for a run most mornings before the meetings started at Newport Beach. Pacific Coast Highway isn’t the most interesting of tracks, but on Tuesday morning I was soon up in Castaways Park, pleasantly jogging through the carefully-nurtured natural coastal vegetation, with views over the ocean and its margin of high-priced homes, slipways, and yachts. I reflected as I ran that we had heard some interesting things about Big Data, but it is now an established topic. There must be something new coming over the horizon.

The answer to what this might be was suggested in the first presentation of that day’s plenary, Mary Ann Mezzapelle, security strategist for HP Enterprise Services, talked about the need to get security right for Big Data and the Cloud. But her scope was actually wider. She spoke of the need to secure the “third platform” – the term coined by IDC to describe the convergence of social, cloud and mobile computing with Big Data.

Securing Big Data

Mary Ann’s keynote was not about the third platform itself, but about what should be done to protect it. The new platform brings with it a new set of security threats, and the increasing scale of operation makes it increasingly important to get the security right. Mary Ann presented a thoughtful analysis founded on a risk-based approach.

She was followed by Adrian Lane, chief technology officer at Securosis, who pointed out that Big Data processing using NoSQL has a different architecture from traditional relational data processing, and requires different security solutions. This does not necessarily mean new techniques; existing techniques can be used in new ways. For example, Kerberos may be used to secure inter-node communications in map/reduce processing. Adrian’s presentation completed the Tuesday plenary sessions.

Service Oriented Architecture

The streams continued after the plenary. I went to the Distributed Services Architecture stream, which focused on SOA.

Bill Poole, enterprise architect at JourneyOne in Australia, described how to use the graphical architecture modeling language ArchiMate® to model service-oriented architectures. He illustrated this using a case study of a global mining organization that wanted to consolidate its two existing bespoke inventory management applications into a single commercial off-the-shelf application. It’s amazing how a real-world case study can make a topic come to life, and the audience certainly responded warmly to Bill’s excellent presentation.

Ali Arsanjani, chief technology officer for Business Performance and Service Optimization, and Heather Kreger, chief technology officer for International Standards, both at IBM, described the range of SOA standards published by The Open Group and available for use by enterprise architects. Ali was one of the brains that developed the SOA Reference Architecture, and Heather is a key player in international standards activities for SOA, where she has helped The Open Group’s Service Integration Maturity Model and SOA Governance Framework to become international standards, and is working on an international standard SOA reference architecture.

Cloud Computing

To start Wednesday’s Cloud Computing streams, TJ Virdi, senior enterprise architect at The Boeing Company, discussed use of TOGAF® to develop an Enterprise Architecture for a Cloud ecosystem. A large enterprise such as Boeing may use many Cloud service providers, enabling collaboration between corporate departments, partners, and regulators in a complex ecosystem. Architecting for this is a major challenge, and The Open Group’s TOGAF for Cloud Ecosystems project is working to provide guidance.

Stuart Boardman of KPN gave a different perspective on Cloud ecosystems, with a case study from the energy industry. An ecosystem may not necessarily be governed by a single entity, and the participants may not always be aware of each other. Energy generation and consumption in the Netherlands is part of a complex international ecosystem involving producers, consumers, transporters, and traders of many kinds. A participant may be involved in several ecosystems in several ways: a farmer for example, might consume energy, have wind turbines to produce it, and also participate in food production and transport ecosystems.

Penelope Gordon of 1-Plug Corporation explained how choice and use of business metrics can impact Cloud service providers. She worked through four examples: a start-up Software-as-a-Service provider requiring investment, an established company thinking of providing its products as cloud services, an IT department planning to offer an in-house private Cloud platform, and a government agency seeking budget for government Cloud.

Mark Skilton, director at Capgemini in the UK, gave a presentation titled “Digital Transformation and the Role of Cloud Computing.” He covered a very broad canvas of business transformation driven by technological change, and illustrated his theme with a case study from the pharmaceutical industry. New technology enables new business models, giving competitive advantage. Increasingly, the introduction of this technology is driven by the business, rather than the IT side of the enterprise, and it has major challenges for both sides. But what new technologies are in question? Mark’s presentation had Cloud in the title, but also featured social and mobile computing, and Big Data.

The New Trend

On Thursday morning I took a longer run, to and round Balboa Island. With only one road in or out, its main street of shops and restaurants is not a through route and the island has the feel of a real village. The SOA Work Group Steering Committee had found an excellent, and reasonably priced, Italian restaurant there the previous evening. There is a clear resurgence of interest in SOA, partly driven by the use of service orientation – the principle, rather than particular protocols – in Cloud Computing and other new technologies. That morning I took the track round the shoreline, and was reminded a little of Dylan Thomas’s “fishing boat bobbing sea.” Fishing here is for leisure rather than livelihood, but I suspected that the fishermen, like those of Thomas’s little Welsh village, spend more time in the bar than on the water.

I thought about how the conference sessions had indicated an emerging trend. This is not a new technology but the combination of four current technologies to create a new platform for enterprise IT: Social, Cloud, and Mobile computing, and Big Data. Mary Ann Mezzapelle’s presentation had referenced IDC’s “third platform.” Other discussions had mentioned Gartner’s “Nexus of forces,” the combination of Social, Cloud and Mobile computing with information that Gartner says is transforming the way people and businesses relate to technology, and will become a key differentiator of business and technology management. Mark Skilton had included these same four technologies in his presentation. Great minds, and analyst corporations, think alike!

I thought also about the examples and case studies in the stream presentations. Areas as diverse as healthcare, manufacturing, energy and policing are using the new technologies. Clearly, they can deliver major business benefits. The challenge for enterprise architects is to maximize those benefits through pragmatic architectures.

Emerging Standards

On the way back to the hotel, I remarked again on what I had noticed before, how beautifully neat and carefully maintained the front gardens bordering the sidewalk are. I almost felt that I was running through a public botanical garden. Is there some ordinance requiring people to keep their gardens tidy, with severe penalties for anyone who leaves a lawn or hedge unclipped? Is a miserable defaulter fitted with a ball and chain, not to be removed until the untidy vegetation has been properly trimmed, with nail clippers? Apparently not. People here keep their gardens tidy because they want to. The best standards are like that: universally followed, without use or threat of sanction.

Standards are an issue for the new enterprise platform. Apart from the underlying standards of the Internet, there really aren’t any. The area isn’t even mapped out. Vendors of Social, Cloud, Mobile, and Big Data products and services are trying to stake out as much valuable real estate as they can. They have no interest yet in boundaries with neatly-clipped hedges.

This is a stage that every new technology goes through. Then, as it matures, the vendors understand that their products and services have much more value when they conform to standards, just as properties have more value in an area where everything is neat and well-maintained.

It may be too soon to define those standards for the new enterprise platform, but it is certainly time to start mapping out the area, to understand its subdivisions and how they inter-relate, and to prepare the way for standards. Following the conference, The Open Group has announced a new Forum, provisionally titled Open Platform 3.0, to do just that.

The SOA and Cloud Work Groups

Thursday was my final day of meetings at the conference. The plenary and streams presentations were done. This day was for working meetings of the SOA and Cloud Work Groups. I also had an informal discussion with Ron Schuldt about a new approach for the UDEF, following up on the earlier UDEF side meeting. The conference hallways, as well as the meeting rooms, often see productive business done.

The SOA Work Group discussed a certification program for SOA professionals, and an update to the SOA Reference Architecture. The Open Group is working with ISO and the IEEE to define a standard SOA reference architecture that will have consensus across all three bodies.

The Cloud Work Group had met earlier to further the TOGAF for Cloud ecosystems project. Now it worked on its forthcoming white paper on business performance metrics. It also – though this was not on the original agenda – discussed Gartner’s Nexus of Forces, and the future role of the Work Group in mapping out the new enterprise platform.

Mapping the New Enterprise Platform

At the start of the conference we looked at how to map the stars. Big Data analytics enables people to visualize the universe in new ways, reach new understandings of what is in it and how it works, and point to new areas for future exploration.

As the conference progressed, we found that Big Data is part of a convergence of forces. Social, mobile, and Cloud Computing are being combined with Big Data to form a new enterprise platform. The development of this platform, and its roll-out to support innovative applications that deliver more business value, is what lies beyond Big Data.

At the end of the conference we were thinking about mapping the new enterprise platform. This will not require sophisticated data processing and analysis. It will take discussions to create a common understanding, and detailed committee work to draft the guidelines and standards. This work will be done by The Open Group’s new Open Platform 3.0 Forum.

The next Open Group conference is in the week of April 15, in Sydney, Australia. I’m told that there’s some great jogging there. More importantly, we’ll be reflecting on progress in mapping Open Platform 3.0, and thinking about what lies ahead. I’m looking forward to it already.

Dr. Chris Harding is Director for Interoperability and SOA at The Open Group. He has been with The Open Group for more than ten years, and is currently responsible for managing and supporting its work on interoperability, including SOA and interoperability aspects of Cloud Computing. He is a member of the BCS, the IEEE and the AEA, and is a certified TOGAF practitioner.

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The Open Group Panel Explores How the Big Data Era Now Challenges the IT Status Quo

By Dana Gardner, Interarbor Solutions

Listen to the recorded podcast here: The Open Group panel explores how the Big Data era now challenges the IT status quo, or view the on-demand video recording on this discussion here: http://new.livestream.com/opengroup/events/1838807.

We recently assembled a panel of experts to explore how Big Data changes the status quo for architecting the enterprise. The bottom line from the discussion is that large enterprises should not just wade into Big Data as an isolated function, but should anticipate the strategic effects and impacts of Big Data — as well the simultaneous complicating factors of Cloud Computing and mobile– as soon as possible.

The panel consisted of Robert Weisman, CEO and Chief Enterprise Architect at Build The Vision; Andras Szakal, Vice President and CTO of IBM’s Federal Division; Jim Hietala, Vice President for Security at The Open Group, and Chris Gerty, Deputy Program Manager at the Open Innovation Program at NASA. I served as the moderator.

And this special thought leadership interview series comes to you in conjunction with The Open Group Conference recently held in Newport Beach, California. The conference focused on “Big Data — he transformation we need to embrace today.”

Threaded factors

An interesting thread for me throughout the conference was to factor where Big Data begins and plain old data, if you will, ends. Of course, it’s going to vary quite a bit from organization to organization.

But Gerty from NASA, part of our panel, provided a good example: It’s when you run out of gas with your old data methods, and your ability to deal with the data — and it’s not just the size of the data itself.

Therefore, Big Data means do things differently — not just to manage the velocity and the volume and the variety of the data, but to really think about data fundamentally and differently. And, we need to think about security, risk and governance. If it’s a “boundaryless organization” when it comes your data, either as a product or service or a resource, that control and management of which data should be exposed, which should be opened, and which should be very closely guarded all need to be factored, determined and implemented.

Here are some excerpts from the on-stage discussion:

Dana Gardner: You mentioned that Big Data to you is not a factor of the size, because NASA’s dealing with so much. It’s when you run out of steam, as it were, with the methodologies. Maybe you could explain more. When do you know that you’ve actually run out of steam with the methodologies?

Gerty: When we collect data, we have some sort of goal in minds of what we might get out of it. When we put the pieces from the data together, it either maybe doesn’t fit as well as you thought or you are successful and you continue to do the same thing, gathering archives of information.

Gardner: Andras, does that square with where you are in your government interactions — that data now becomes a different type of resource, and that you need to know when to do things differently?At that point, where you realize there might even something else that you want to do with the data, different than what you planned originally, that’s when we have to pivot a little bit and say, “Now I need to treat this as a living archive. It’s a ‘it may live beyond me’ type of thing.” At that point, I think you treat it as setting up the infrastructure for being used later, whether it’d be by you or someone else. That’s an important transition to make and might be what one could define as Big Data.

Szakal: The importance of data hasn’t changed. The data itself, the veracity of the data, is still important. Transactional data will always need to exist. The difference is that you have certainly the three or four Vs, depending on how you look at it, but the importance of data is in its veracity, and your ability to understand or to be able to use that data before the data’s shelf life runs out.

Gardner: Bob, we’ve seen the price points on storage go down so dramatically. We’ve seem people just decide to hold on to data that they wouldn’t have before, simply because they can and they can afford to do so. That means we need to try to extract value and use that data. From the perspective of an enterprise architect, how are things different now, vis-à-vis this much larger set of data and variety of data, when it comes to planning and executing as architects?Some data has a shelf life that’s long lived. Other data has very little shelf life, and you would use different approaches to being able to utilize that information. It’s ultimately not about the data itself, but it’s about gaining deep insight into that data. So it’s not storing data or manipulating data, but applying those analytical capabilities to data.

Weisman: One of the major issues is that normally organizations are holding two orders of magnitude more data then they need. It’s an huge overhead, both in terms of the applications architecture that has a code basis, larger than it should be, and also from the technology architecture that is supporting a horrendous number of servers and a whole bunch of technology stuff that they don’t need.

The issue for the architect is to figure out as what data is useful, institute a governance process, so that you can have data lifecycle management, have a proper disposition,  focus the organization on information data and knowledge that is basically going to provide business value to the organization, and help them innovate and have a competitive advantage.

Can’t afford it

And in terms of government, just improve service delivery, because there’s waste right now on information infrastructure, and we can’t afford it anymore.

Gardner: So it’s difficult to know what to keep and what not to keep. I’ve actually spoken to a few people lately who want to keep everything, just because they want to mine it, and they are willing to spend the money and effort to do that.

Jim Hietala, when people do get to this point of trying to decide what to keep, what not to keep, and how to architect properly for that, they also need to factor in security. It shouldn’t become later in the process. It should come early. What are some of the precepts that you think are important in applying good security practices to Big Data?

Hietala: One of the big challenges is that many of the big-data platforms weren’t built from the get-go with security in mind. So some of the controls that you’ve had available in your relational databases, for instance, you move over to the Big Data platforms and the access control authorizations and mechanisms are not there today.

Gardner: There are a lot of unknown unknowns out there, as we discovered with our tweet chat last month. Some people think that the data is just data, and you apply the same security to it. Do you think that’s the case with Big Data? Is it just another follow-through of what you always did with data in the first place?Planning the architecture, looking at bringing in third-party controls to give you the security mechanisms that you are used to in your older platforms, is something that organizations are going to have to do. It’s really an evolving and emerging thing at this point.

Hietala: I would say yes, at a conceptual level, but it’s like what we saw with virtualization. When there was a mad rush to virtualize everything, many of those traditional security controls didn’t translate directly into the virtualized world. The same thing is true with Big Data.

When you’re talking about those volumes of data, applying encryption, applying various security controls, you have to think about how those things are going to scale? That may require new solutions from new technologies and that sort of thing.

Gardner: Chris Gerty, when it comes to that governance, security, and access control, are there any lessons that you’ve learned that you are aware of in terms of the best of openness, but also with the ability to manage the spigot?

Gerty: Spigot is probably a dangerous term to use, because it implies that all data is treated the same. The sooner that you can tag the data as either sensitive or not, mostly coming from the person or team that’s developed or originated the data, the better.

Kicking the can

Once you have it on a hard drive, once you get crazy about storing everything, if you don’t know where it came from, you’re forced to put it into a secure environment. And that’s just kicking the can down the road. It’s really a disservice to people who might use the data in a useful way to address their problems.

We constantly have satellites that are made for one purpose. They send all the data down. It’s controlled either for security or for intellectual property (IP), so someone can write a paper. Then, after the project doesn’t get funded or it just comes to a nice graceful close, there is that extra step, which is almost a responsibility of the originators, to make it useful to the rest of the world.

Gardner: Let’s look at Big Data through the lens of some other major trends right now. Let’s start with Cloud. You mentioned that at NASA, you have your own private Cloud that you’re using a lot, of course, but you’re also now dabbling in commercial and public Clouds. Frankly, the price points that these Cloud providers are offering for storage and data services are pretty compelling.

So we should expect more data to go to the Cloud. Bob, from your perspective, as organizations and architects have to think about data in this hybrid Cloud on-premises off-premises, moving back and forth, what do you think enterprise architects need to start thinking about in terms of managing that, planning for the right destination of data, based on the right mix of other requirements?

Weisman: It’s a good question. As you said, the price point is compelling, but the security and privacy of the information is something else that has to be taken into account. Where is that information going to reside? You have to have very stringent service-level agreements (SLAs) and in certain cases, you might say it’s a price point that’s compelling, but the risk analysis that I have done means that I’m going to have to set up my own private Cloud.

Gardner: Andras, how do the Cloud and Big Data come together in a way that’s intriguing to you?Right now, everybody’s saying is the public Cloud is going to be the way to go. Vendors are going to have to be very sensitive to that and many are, at this point in time, addressing a lot of the needs of some of the large client basis. So it’s not one-size-fits-all and it’s more than just a price for service. Architecture can bring down the price pretty dramatically, even within an enterprise.

Szakal: Actually it’s a great question. We could take the rest of the 22 minutes talking on this one question. I helped lead the President’s Commission on Big Data that Steve Mills from IBM and — I forget the name of the executive from SAP — led. We intentionally tried to separate Cloud from Big Data architecture, primarily because we don’t believe that, in all cases, Cloud is the answer to all things Big Data. You have to define the architecture that’s appropriate for your business needs.

However, it also depends on where the data is born. Take many of the investments IBM has made into enterprise market management, for example, Coremetrics, several of these services that we now offer for helping customers understand deep insight into how their retail market or supply chain behaves.

Born in the Cloud

All of that information is born in the Cloud. But if you’re talking about actually using Cloud as infrastructure and moving around huge sums of data or constructing some of these solutions on your own, then some of the ideas that Bob conveyed are absolutely applicable.

I think it becomes prohibitive to do that and easier to stand up a hybrid environment for managing the amount of data. But I think that you have to think about whether your data is real-time data, whether it’s data that you could apply some of these new technologies like Hadoop to, Hadoop MapReduce-type solutions, or whether it’s traditional data warehousing.

Data warehouses are going to continue to exist and they’re going to continue to evolve technologically. You’re always going to use a subset of data in those data warehouses, and it’s going to be an applicable technology for many years to come.

Gardner: So suffice it to say, an enterprise architect who is well versed in both Cloud infrastructure requirements, technologies, and methods, as well as Big Data, will probably be in quite high demand. That specialization in one or the other isn’t as valuable as being able to cross-pollinate between them.

Szakal: Absolutely. It’s enabling our architects and finding deep individuals who have this unique set of skills, analytics, mathematics, and business. Those individuals are going to be the future architects of the IT world, because analytics and Big Data are going to be integrated into everything that we do and become part of the business processing.

Gardner: Well, that’s a great segue to the next topic that I am interested in, and it’s around mobility as a trend and also application development. The reason I lump them together is that I increasingly see developers being tasked with mobile first.

When you create a new app, you have to remember that this is going to run in the mobile tier and you want to make sure that the requirements, the UI, and the complexity of that app don’t go beyond the ability of the mobile app and the mobile user. This is interesting to me, because data now has a different relationship with apps.

We used to think of apps as creating data and then the data would be stored and it might be used or integrated. Now, we have applications that are simply there in order to present the data and we have the ability now to present it to those mobile devices in the mobile tier, which means it goes anywhere, everywhere all the time.

Let me start with you Jim, because it’s security and risk, but it’s also just rethinking the way we use data in a mobile tier. If we can do it safely, and that’s a big IF, how important should it be for organizations to start thinking about making this data available to all of these devices and just pour out into that mobile tier as possible?

Hietala: In terms of enabling the business, it’s very important. There are a lot of benefits that accrue from accessing your data from whatever device you happen to be on. To me, it is that question of “if,” because now there’s a whole lot of problems to be solved relative to the data floating around anywhere on Android, iOS, whatever the platform is, and the organization being able to lock down their data on those devices, forgetting about whether it’s the organization device or my device. There’s a set of issues around that that the security industry is just starting to get their arms around today.

Mobile ability

Gardner: Chris, any thoughts about this mobile ability that the data gets more valuable the more you can use it and apply it, and then the more you can apply it, the more data you generate that makes the data more valuable, and we start getting into that positive feedback loop?

Gerty: Absolutely. It’s almost an appreciation of what more people could do and get to the problem. We’re getting to the point where, if it’s available on your desktop, you’re going to find a way to make it available on your device.

That same security questions probably need to be answered anyway, but making it mobile compatible is almost an acknowledgment that there will be someone who wants to use it. So let me go that extra step to make it compatible and see what I get from them. It’s more of a cultural benefit that you get from making things compatible with mobile.

Gardner: Any thoughts about what developers should be thinking by trying to bring the fruits of Big Data through these analytics to more users rather than just the BI folks or those that are good at SQL queries? Does this change the game by actually making an application on a mobile device, simple, powerful but accessing this real time updated treasure trove of data?

Gerty: I always think of the astronaut on the moon. He’s got a big, bulky glove and he might have a heads-up display in front of him, but he really needs to know exactly a certain piece of information at the right moment, dealing with bandwidth issues, dealing with the environment, foggy helmet wherever.

It’s very analogous to what the day-to-day professional will use trying to find out that quick e-mail he needs to know or which meeting to go to — which one is more important — and it all comes down to putting your developer in the shoes of the user. So anytime you can get interaction between the two, that’s valuable.

Weisman: From an Enterprise Architecture point of view my background is mainly defense and government, but defense mobile computing has been around for decades. So you’ve always been dealing with that.

The main thing is that in many cases, if they’re coming up with information, the whole presentation layer is turning into another architecture domain with information visualization and also with your security controls, with an integrated identity management capability.

It’s like you were saying about astronaut getting it right. He doesn’t need to know everything that’s happening in the world. He needs to know about his heads-up display, the stuff that’s relevant to him.

So it’s getting the right information to person in an authorized manner, in a way that he can visualize and make sense of that information, be it straight data, analytics, or whatever. The presentation layer, ergonomics, visual communication are going to become very important in the future for that. There are also a lot of problems. Rather than doing it at the application level, you’re doing it entirely in one layer.

Governance and security

Gardner: So clearly the implications of data are cutting across how we think about security, how we think about UI, how we factor in mobility. What we now think about in terms of governance and security, we have to do differently than we did with older data models.

Jim Hietala, what about the impact on spurring people towards more virtualized desktop delivery, if you don’t want to have the date on that end device, if you want solve some of the issues about control and governance, and if you want to be able to manage just how much data gets into that UI, not too much not too little.

Do you think that some of these concerns that we’re addressing will push people to look even harder, maybe more aggressive in how they go to desktop and application virtualization, as they say, keep it on the server, deliver out just the deltas?

Hietala: That’s an interesting point. I’ve run across a startup in the last month or two that is doing is that. The whole value proposition is to virtualize the environment. You get virtual gold images. You don’t have to worry about what’s actually happening on the physical device and you know when the devices connect. The security threat goes away. So we may see more of that as a solution to that.

Gardner: Andras, do you see that that some of the implications of Big Data, far fetched as it may be, are propelling people to cultivate their servers more and virtualize their apps, their data, and their desktop right up to the end devices?

Szakal: Yeah, I do. I see IBM providing solutions for virtual desktop, but I think it was really a security question you were asking. You’re certainly going to see an additional number of virtualized desktop environments.

Ultimately, our network still is not stable enough or at a high enough bandwidth to really make that useful exercise for all but the most menial users in the enterprise. From a security point of view, there is a lot to be still solved.

And part of the challenge in the Cloud environment that we see today is the proliferation of virtual machines (VMs) and the inability to actually contain the security controls within those machines and across these machines from an enterprise perspective. So we’re going to see more solutions proliferate in this area and to try to solve some of the management issues, as well as the security issues, but we’re a long ways away from that.

Gerty: Big Data, by itself, isn’t magical. It doesn’t have the answers just by being big. If you need more, you need to pry deeper into it. That’s the example. They realized early enough that they were able to make something good.

Gardner: Jim Hietala, any thoughts about examples that illustrate where we’re going and why this is so important?

Hietala: Being a security guy, I tend to talk about scare stories, horror stories. One example from last year that struck me. One of the major retailers here in the U.S. hit the news for having predicted, through customer purchase behavior, when people were pregnant.

They could look and see, based upon buying 20 things, that if you’re buying 15 of these and your purchase behavior has changed, they can tell that. The privacy implications to that are somewhat concerning.

An example was that this retailer was sending out coupons related to somebody being pregnant. The teenage girl, who was pregnant hadn’t told her family yet. The father found it. There was alarm in the household and at the local retailer store, when the father went and confronted them.

Privacy implications

There are privacy implications from the use of Big Data. When you get powerful new technology in marketing people’s hands, things sometimes go awry. So I’d throw that out just as a cautionary tale that there is that aspect to this. When you can see across people’s buying transactions, things like that, there are privacy considerations that we’ll have to think about, and that we really need to think about as an industry and a society.

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Open Group Panel Explores Changing Field of Risk Management and Analysis in the Era of Big Data

By Dana Gardner, Interarbor Solutions

Listen to the recorded podcast here: The Open Group Panel Explores Changing Field of Risk Management and Analysis in Era of Big Data

This is a transcript of a sponsored podcast discussion on the threats from and promise of Big Data in securing enterprise information assets in conjunction with the The Open Group Conference in Newport Beach.

Dana Gardner: Hello, and welcome to a special thought leadership interview series coming to you in conjunction with The Open Group Conference on January 28 in Newport Beach, California.

I’m Dana Gardner, Principal Analyst at Interarbor Solutions, and I’ll be your host and moderator throughout these business transformation discussions. The conference itself is focusing on Big Data the transformation we need to embrace today.

We’re here now with a panel of experts to explore new trends and solutions in the area of risk management and analysis. We’ll learn how large enterprises are delivering risk assessments and risk analysis, and we’ll see how Big Data can be both an area to protect from in form of risks, but also as a tool for better understanding and mitigating risks.

With that, please join me in welcoming our panel. We’re here with Jack Freund, PhD, the Information Security Risk Assessment Manager at TIAA-CREF. Welcome, Jack.

Jack Freund: Hello Dana, how are you?

Gardner: I’m great. Glad you could join us.

We are also here with Jack Jones, Principal of CXOWARE. He has more than nine years of experience as a Chief Information Security Officer, is the inventor of the Factor Analysis Information Risk (FAIR) framework. Welcome, Jack.

Jack Jones: Thank you. And we’re also here with Jim Hietala, Vice President, Security for The Open Group. Welcome, Jim.

Jim Hietala: Thanks, Dana.

Gardner: All right, let’s start out with looking at this from a position of trends. Why is the issue of risk analysis so prominent now? What’s different from, say, five years ago? And we’ll start with you, Jack Jones.

Jones: The information security industry has struggled with getting the attention of and support from management and businesses for a long time, and it has finally come around to the fact that the executives care about loss exposure — the likelihood of bad things happening and how bad those things are likely to be.

It’s only when we speak of those terms or those issues in terms of risk, that we make sense to those executives. And once we do that, we begin to gain some credibility and traction in terms of getting things done.

Gardner: So we really need to talk about this in the terms that a business executive would appreciate, not necessarily an IT executive.

Effects on business

Jones: Absolutely. They’re tired of hearing about vulnerabilities, hackers, and that sort of thing. It’s only when we can talk in terms of the effect on the business that it makes sense to them.

Gardner: Jack Freund, I should also point out that you have more than 14 years in enterprise IT experience. You’re a visiting professor at DeVry University and you chair a risk-management subcommittee for ISACA? Is that correct?

Freund: ISACA, yes.

Gardner: And do you agree?

Freund: The problem that we have as a profession, and I think it’s a big problem, is that we have allowed ourselves to escape the natural trend that the other IT professionals have already taken.

There was a time, years ago, when you could code in the basement, and nobody cared much about what you were doing. But now, largely speaking, developers and systems administrators are very focused on meeting the goals of the organization.

Security has been allowed to miss that boat a little. We have been allowed to hide behind this aura of a protector and of an alerter of terrible things that could happen, without really tying ourselves to the problem that the organizations are facing and how can we help them succeed in what they’re doing.

Gardner: Jim Hietala, how do you see things that are different now than a few years ago when it comes to risk assessment?

Hietala: There are certainly changes on the threat side of the landscape. Five years ago, you didn’t really have hacktivism or this notion of an advanced persistent threat (APT).

That highly skilled attacker taking aim at governments and large organizations didn’t really exist -– or didn’t exist to the degree it does today. So that has changed.

You also have big changes to the IT platform landscape, all of which bring new risks that organizations need to really think about. The mobility trend, the Cloud trend, the big-data trend that we are talking about today, all of those things bring new risk to the organization.

As Jack Jones mentioned, business executives don’t want to hear about, “I’ve got 15 vulnerabilities in the mobility part of my organization.” They want to understand what’s the risk of bad things happening because of mobility, what we’re doing about it, and what’s happening to risk over time?

So it’s a combination of changes in the threats and attackers, as well as just changes to the IT landscape, that we have to take a different look at how we measure and present risk to the business.

Gardner: Because we’re at a big-data conference, do you share my perception, Jack Jones, that Big Data can be a source of risk and vulnerability, but also the analytics and the business intelligence (BI) tools that we’re employing with Big Data can be used to alert you to risks or provide a strong tool for better understanding your true risk setting or environment.

Crown jewels

Jones: You are absolutely right. You think of Big Data and, by definition, it’s where your crown jewels, and everything that leads to crown jewels from an information perspective, are going to be found. It’s like one-stop shopping for the bad guy, if you want to look at it in that context. It definitely needs to be protected. The architecture surrounding it and its integration across a lot of different platforms and such, can be leveraged and probably result in a complex landscape to try and secure.

There are a lot of ways into that data and such, but at least if you can leverage that same Big Data architecture, it’s an approach to information security. With log data and other threat and vulnerability data and such, you should be able to make some significant gains in terms of how well-informed your analyses and your decisions are, based on that data.

Gardner: Jack Freund, do you share that? How does Big Data fit into your understanding of the evolving arena of risk assessment and analysis?

Freund: If we fast-forward it five years, and this is even true today, a lot of people on the cutting edge of Big Data will tell you the problem isn’t so much building everything together and figuring out what it can do. They are going to tell you that the problem is what we do once we figure out everything that we have. This is the problem that we have traditionally had on a much smaller scale in information security. When everything is important, nothing is important.

Gardner: To follow up on that, where do you see the gaps in risk analysis in large organizations? In other words, what parts of organizations aren’t being assessed for risk and should be?

Freund: The big problems that exist largely today in the way that risk assessments are done, is the focus on labels. We want to quickly address the low, medium, and high things and know where they are. But the problem is that there are inherent problems in the way that we think about those labels, without doing any of the analysis legwork.

I think that’s what’s really missing is that true analysis. If the system goes offline, do we lose money? If the system becomes compromised, what are the cost-accounting things that will happen that allow us to figure out how much money we’re going to lose.

That analysis work is largely missing. That’s the gap. The gap is if the control is not in place, then there’s a risk that must be addressed in some fashion. So we end up with these very long lists of horrible, terrible things that can be done to us in all sorts of different ways, without any relevance to the overall business of the organization.

Every day, our organizations are out there selling products, offering services, which is and of itself, its own risky venture. So tying what we do from an information security perspective to that is critical for not just the success of the organization, but the success of our profession.

Gardner: So we can safely say that large companies are probably pretty good at a cost-benefit analysis or they wouldn’t be successful. Now, I guess we need to ask them to take that a step further and do a cost-risk analysis, but in business terms, being mindful that their IT systems might be a much larger part of that than they had at once considered. Is that fair, Jack?

Risk implications

Jones: Businesses have been making these decisions, chasing the opportunity, but generally, without any clear understanding of the risk implications, at least from the information security perspective. They will have us in the corner screaming and throwing red flags in there, and talking about vulnerabilities and threats from one thing or another.

But, we come to the table with red, yellow, and green indicators, and on the other side of the table, they’ve got numbers. Well, here is what we expect to earn in revenue from this initiative, and the information security people are saying it’s crazy. How do you normalize the quantitative revenue gain versus red, yellow, and green?

Gardner: Jim Hietala, do you see it in the same red, yellow, green or are there some other frameworks or standard methodologies that The Open Group is looking at to make this a bit more of a science?

Hietala: Probably four years ago, we published what we call the Risk Taxonomy Standard which is based upon FAIR, the management framework that Jack Jones invented. So, we’re big believers in bringing that level of precision to doing risk analysis. Having just gone through training for FAIR myself, as part of the standards effort that we’re doing around certification, I can say that it really brings a level of precision and a depth of analysis to risk analysis that’s been lacking frequently in IT security and risk management.

Gardner: We’ve talked about how organizations need to be mindful that their risks are higher and different than in the past and we’ve talked about how standardization and methodologies are important, helping them better understand this from a business perspective, instead of just a technology perspective.

But, I’m curious about a cultural and organizational perspective. Whose job should this fall under? Who is wearing the white hat in the company and can rally the forces of good and make all the bad things managed? Is this a single person, a cultural, an organizational mission? How do you make this work in the enterprise in a real-world way? Let’s go to you, Jack Freund.

Freund: The profession of IT risk management is changing. That profession will have to sit between the business and information security inclusive of all the other IT functions that make that happen.

In order to be successful sitting between these two groups, you have to be able to speak the language of both of those groups. You have to be able to understand profit and loss and capital expenditure on the business side. On the IT risk side, you have to be technical enough to do all those sorts of things.

But I think the sum total of those two things is probably only about 50 percent of the job of IT risk management today. The other 50 percent is communication. Finding ways to translate that language and to understand the needs and concerns of each side of that relationship is really the job of IT risk management.

To answer your question, I think it’s absolutely the job of IT risk management to do that. From my own experiences with the FAIR framework, I can say that using FAIR is the Rosetta Stone for speaking between those two groups.

Necessary tools

It gives you the tools necessary to speak in the insurance and risk terms that business appreciate. And it gives you the ability to be as technical and just nerdy, if you will, as you need to be in order to talk to IT security and the other IT functions in order to make sure everybody is on the same page and everyone feels like their concerns are represented in the risk-assessment functions that are happening.

Gardner: Jack Jones, can you add to that?

Jones: I agree with what Jack said wholeheartedly. I would add, though, that integration or adoption of something like this is a lot easier the higher up in the organization you go.

For CFOs traditionally, their neck is most clearly on the line for risk-related issues within most organizations. At least in my experience, if you get their ear on this and present the information security data analyses to them, they jump on board, they drive it through the organization, and it’s just brain-dead easy.

If you try to drive it up through the ranks, maybe you get an enthusiastic supporter in the information security organization, especially if it’s below the CISO level, and they try a grassroots sort of effort to bring it in, it’s a tougher thing. It can still work. I’ve seen it work very well, but, it’s a longer row to hoe.

Gardner: There have been a lot of research, studies, and surveys on data breaches. What are some of the best sources, or maybe not so good sources, for actually measuring this? How do you know if you’re doing it right? How do you know if you’re moving from yellow to green, instead of to red? To you, Jack Freund.

Freund: There are a couple of things in that question. The first is there’s this inherent assumption in a lot of organizations that we need to move from yellow to green, and that may not be the case. So, becoming very knowledgeable about the risk posture and the risk tolerance of the organization is a key.

That’s part of the official mindset of IT security. When you graduate an information security person today, they are minted knowing that there are a lot of bad things out there, and their goal in life is to reduce them. But, that may not be the case. The case may very well be that things are okay now, but we have bigger things to fry over here that we’re going to focus on. So, that’s one thing.

The second thing, and it’s a very good question, is how we know that we’re getting better? How do we trend that over time? Overall, measuring that value for the organization has to be able to show a reduction of a risk or at least reduction of risk to the risk-tolerance levels of the organization.

Calculating and understanding that requires something that I always phrase as we have to become comfortable with uncertainty. When you are talking about risk in general, you’re talking about forward-looking statements about things that may or may not happen. So, becoming comfortable with the fact that they may or may not happen means that when you measure them today, you have to be willing to be a little bit squishy in how you’re representing that.

In FAIR and in other academic works, they talk about using ranges to do that. So, things like high, medium, and low, could be represented in terms of a minimum, maximum, and most likely. And that tends to be very, very effective. People can respond to that fairly well.

Gathering data

Jones: With regard to the data sources, there are a lot of people out there doing these sorts of studies, gathering data. The problem that’s hamstringing that effort is the lack of a common set of definitions, nomenclature, and even taxonomy around the problem itself.

You will have one study that will have defined threat, vulnerability, or whatever differently from some other study, and so the data can’t be normalized. It really harms the utility of it. I see data out there and I think, “That looks like that can be really useful.” But, I hesitate to use it because I don’t understand. They don’t publish their definitions, approach, and how they went after it.

There’s just so much superficial thinking in the profession on this that we now have dug under the covers. Too often, I run into stuff that just can’t be defended. It doesn’t make sense, and therefore the data can’t be used. It’s an unfortunate situation.

I do think we’re heading in a positive direction. FAIR can provide a normalizing structure for that sort of thing. The VERIS framework, which by the way, is also derived in part from FAIR, also has gained real attraction in terms of the quality of the research they have done and the data they’re generating. We’re headed in the right direction, but we’ve got a long way to go.

Gardner: Jim Hietala, we’re seemingly looking at this on a company-by-company basis. But, is there a vertical industry slice or industry-wide slice where we could look at what’s happening to everyone and put some standard understanding, or measurement around what’s going on in the overall market, maybe by region, maybe by country?

Hietala: There are some industry-specific initiatives and what’s really needed, as Jack Jones mentioned, are common definitions for things like breach, exposure, loss, all those, so that the data sources from one organization can be used in another, and so forth. I think about the financial services industry. I know that there is some information sharing through an organization called the FS-ISAC about what’s happening to financial services organizations in terms of attacks, loss, and those sorts of things.

There’s an opportunity for that on a vertical-by-vertical basis. But, like Jack said, there is a long way to go on that. In some industries, healthcare for instance, you are so far from that, it’s ridiculous. In the US here, the HIPAA security rule says you must do a risk assessment. So, hospitals have done annual risk assessments, will stick the binder on the shelf, and they don’t think much about information security in between those annual risk assessments. That’s a generalization, but various industries are at different places on a continuum of maturity of their risk management approaches.

Gardner: As we get better with having a common understanding of the terms and the measurements and we share more data, let’s go back to this notion of how to communicate this effectively to those people that can use it and exercise change management as a result. That could be the CFO, the CEO, what have you, depending on the organization.

Do you have any examples? Can we look to an organization that’s done this right, and examine their practices, the way they’ve communicated it, some of the tools they’ve used and say, “Aha, they’re headed in the right direction maybe we could follow a little bit.” Let’s start with you, Jack Freund.

Freund: I have worked and consulted for various organizations that have done risk management at different levels. The ones that have embraced FAIR tend to be the ones that overall feel that risk is an integral part of their business strategy. And I can give a couple of examples of scenarios that have played out that I think have been successful in the way they have been communicated.

Coming to terms

The key to keep in mind with this is that one of the really important things is that when you’re a security professional, you’re again trained to feel like you need results. But, the results for the IT risk management professional are different. The results are “I’ve communicated this effectively, so I am done.” And then whatever the results are, are the results that needed to be. And that’s a really hard thing to come to terms with.

I’ve been involved in large-scale efforts to assess risk for a Cloud venture. We needed to move virtually every confidential record that we have to the Cloud in order to be competitive with the rest of our industry. If our competitors are finding ways to utilize the Cloud before us, we can lose out. So, we need to find a way to do that, and to be secure and compliant with all the laws and regulations and such.

Through that scenario, one of the things that came out was that key ownership became really, really important. We had the opportunity to look at the various control structures and we analyzed them using FAIR. What we ended up with was sort of a long-tail risk. Most people will probably do their job right over a long enough period of time. But, over that same long period of time, the odds of somebody making a mistake not in your favor are probably likely, but, not significantly enough so that you can’t make the move.

But, the problem became that the loss side, the side that typically gets ignored with traditional risk-assessment methodologies, was so significant that the organization needed to make some judgment around that, and they needed to have a sense of what we needed to do in order to minimize that.

That became a big point of discussion for us and it drove the conversation away from bad things could happen. We didn’t bury the lead. The lead was that this is the most important thing to this organization in this particular scenario.

So, let’s talk about things we can do. Are we comfortable with it? Do we need to make any sort of changes? What are some control opportunities? How much do they cost? This is a significantly more productive conversation than just, “Here is a bunch of bad things that happen. I’m going to cross my arms and say no.”

Gardner: Jack Jones, examples at work?

Jones: In an organization that I’ve been working with recently, their board of directors said they wanted a quantitative view of information security risk. They just weren’t happy with the red, yellow, green. So, they came to us, and there were really two things that drove them there. One was that they were looking at cyber insurance. They wanted to know how much cyber insurance they should take out, and how do you figure that out when you’ve got a red, yellow, green scale?

They were able to do a series of analyses on a population of the scenarios that they thought were relevant in their world, get an aggregate view of their annualized loss exposure, and make a better informed decision about that particular problem.

Gardner: I’m curious how prevalent cyber insurance is, and is that going to be a leveling effect in the industry where people speak a common language the equivalent of actuarial tables, but for security in enterprise and cyber security?

Jones: One would dream and hope, but at this point, what I’ve seen out there in terms of the basis on which insurance companies are setting their premiums and such is essentially the same old “risk assessment” stuff that the industry has been doing poorly for years. It’s not based on data or any real analysis per se, at least what I’ve run into. What they do is set their premiums high to buffer themselves and typically cover as few things as possible. The question of how much value it’s providing the customers becomes a problem.

Looking to the future

Gardner: We’re coming up on our time limit. So, let’s quickly look to the future. Is there such thing as risk management as a service? Can we outsource this? Is there a way in which moving more of IT into Cloud or hybrid models would mitigate risk, because the Cloud provider would standardize? Then, many players in that environment, those who were buying those services, would be under that same umbrella? Let’s start with you Jim Hietala. What’s the future of this and what do the Cloud trends bring to the table?

Hietala: I’d start with a maxim that comes out of the financial services industry, which is that you can outsource the function, but you still own the risk. That’s an unfortunate reality. You can throw things out in the Cloud, but it doesn’t absolve you from understanding your risk and then doing things to manage it to transfer it if there’s insurance or whatever the case may be.

That’s just a reality. Organizations in the risky world we live in are going to have to get more serious about doing effective risk analysis. From The Open Group standpoint, we see this as an opportunity area.

As I mentioned, we’ve standardized the taxonomy piece of FAIR. And we really see an opportunity around the profession going forward to help the risk-analysis community by further standardizing FAIR and launching a certification program for a FAIR-certified risk analyst. That’s in demand from large organizations that are looking for evidence that people understand how to apply FAIR and use it in doing risk analyses.

Gardner: Jack Freund, looking into your crystal ball, how do you see this discipline evolving?

Freund: I always try to consider things as they exist within other systems. Risk is a system of systems. There are a series of pressures that are applied, and a series of levers that are thrown in order to release that sort of pressure.

Risk will always be owned by the organization that is offering that service. If we decide at some point that we can move to the Cloud and all these other things, we need to look to the legal system. There is a series of pressures that they are going to apply, and who is going to own that, and how that plays itself out.

If we look to the Europeans and the way that they’re managing risk and compliance, they’re still as strict as we in United States think that they may be about things, but there’s still a lot of leeway in a lot of the ways that laws are written. You’re still being asked to do things that are reasonable. You’re still being asked to do things that are standard for your industry. But, we’d still like the ability to know what that is, and I don’t think that’s going to go away anytime soon.

Judgment calls

We’re still going to have to make judgment calls. We’re still going to have to do 100 things with a budget for 10 things. Whenever that happens, you have to make a judgment call. What’s the most important thing that I care about? And that’s why risk management exists, because there’s a certain series of things that we have to deal with. We don’t have the resources to do them all, and I don’t think that’s going to change over time. Regardless of whether the landscape changes, that’s the one that remains true.

Gardner: The last word to you, Jack Jones. It sounds as if we’re continuing down the path of being mostly reactive. Is there anything you can see on the horizon that would perhaps tip the scales, so that the risk management and analysis practitioners can really become proactive and head things off before they become a big problem?

Jones: If we were to take a snapshot at any given point in time of an organization’s loss exposure, how much risk they have right then, that’s a lagging indicator of the decisions they’ve made in the past, and their ability to execute against those decisions.

We can do some great root-cause analysis around that and ask how we got there. But, we can also turn that coin around and ask how good we are at making well-informed decisions, and then executing against them, the asking what that implies from a risk perspective downstream.

If we understand the relationship between our current state, and past and future states, we have those linkages defined, especially, if we have an analytic framework underneath it. We can do some marvelous what-if analysis.

What if this variable changed in our landscape? Let’s run a few thousand Monte Carlo simulations against that and see what comes up. What does that look like? Well, then let’s change this other variable and then see which combination of dials, when we turn them, make us most robust to change in our landscape.

But again, we can’t begin to get there, until we have this foundational set of definitions, frameworks, and such to do that sort of analysis. That’s what we’re doing with FAIR, but without some sort of framework like that, there’s no way you can get there.

Gardner: I am afraid we’ll have to leave it there. We’ve been talking with a panel of experts on how new trends and solutions are emerging in the area of risk management and analysis. And we’ve seen how new tools for communication and using Big Data to understand risks are also being brought to the table.

This special BriefingsDirect discussion comes to you in conjunction with The Open Group Conference in Newport Beach, California. I’d like to thank our panel: Jack Freund, PhD, Information Security Risk Assessment Manager at TIAA-CREF. Thanks so much Jack.

Freund: Thank you, Dana.

Gardner: We’ve also been speaking with Jack Jones, Principal at CXOWARE.

Jones: Thank you. Thank you, pleasure to be here.

Gardner: And last, Jim Hietala, the Vice President for Security at The Open Group. Thanks.

Hietala: Thanks, Dana.

Gardner: This is Dana Gardner, Principal Analyst at Interarbor Solutions; your host and moderator through these thought leadership interviews. Thanks again for listening and come back next time.

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On Demand Broadcasts from Day One at The Open Group Conference in Newport Beach

By The Open Group Conference Team

Since not everyone could make the trip to The Open Group Conference in Newport Beach, we’ve put together a recap of day one’s plenary speakers. Stay tuned for more recaps coming soon!

Big Data at NASA

In his talk titled, “Big Data at NASA,” Chris Gerty, deputy program manager, Open Innovation Program, National Aeronautics and Space Administration (NASA), discussed how Big Data is being interpreted by the next generation of rocket scientists. Chris presented a few lessons learned from his experiences at NASA:

  1. A traditional approach is not always the best approach. A tried and proven method may not translate. Creating more programs for more data to store on bigger hard drives is not always effective. We need to address the never-ending challenges that lie ahead in the shift of society to the information age.
  2. A plan for openness. Based on a government directive, Chris’ team looked to answer questions by asking the right people. For example, NASA asked the people gathering data on a satellite to determine what data was the most important, which enabled NASA to narrow focus and solve problems. Furthermore, by realizing what can also be useful to the public and what tools have already been developed by the public, open source development can benefit the masses. Through collaboration, governments and citizens can work together to solve some of humanity’s biggest problems.
  3. Embrace the enormity of the universe. Look for Big Data where no one else is looking by putting sensors and information gathering tools. If people continue to be scared of Big Data, we will be resistant to gathering more of it. By finding Big Data where it has yet to be discovered, we can solve problems and innovate.

To view Chris’s presentation, please watch the broadcasted session here: http://new.livestream.com/opengroup/Gerty-NPB13

Bringing Order to the Chaos

David Potter, chief technical officer at Promise Innovation and Ron Schuldt, senior partner at UDEF-IT, LLC discussed how The Open Group’s evolving Quantum Lifecycle Management (QLM) standard coupled with its complementary Universal Data Element Framework (UDEF) standard help bring order to the terminology chaos that faces Big Data implementations.

The QLM standard provides a framework for the aggregation of lifecycle data from a multiplicity of sources to add value to the decision making process. Gathering mass amounts of data is useless if it cannot be analyzed. The QLM framework provides a means to interpret the information gathered for business intelligence. The UDEF allows each piece of data to be paired with an unambiguous key to provide clarity. By partnering with the UDEF, the QLM framework is able to separate itself from domain-specific semantic models. The UDEF also provides a ready-made key for international language support. As an open standard, the UDEF is data model independent and as such supports normalization across data models.

One example of successful implementation is by Compassion International. The organization needed to find a balance between information that should be kept internal (e.g., payment information) and information that should be shared with its international sponsors. In this instance, UDEF was used as a structured process for harmonizing the terms used in IT systems between funding partners.

The beauty of the QLM framework and UDEF integration is that they are flexible and can be applied to any product, domain and industry.

To view David and Ron’s presentation, please watch the broadcasted session here: http://new.livestream.com/opengroup/potter-NPB13

Big Data – Panel Discussion

Moderated by Dana Gardner, Interarbor Solution, Robert Weisman , Build The Vision, Andras Szakal, IBM, Jim Hietala, The Open Group, and Chris Gerty, NASA, discussed the implications of Big Data and what it means for business architects and enterprise architects.

Big Data is not about the size but about analyzing that data. Robert mentioned that most organizations store more data than they need or use, and from an enterprise architect’s perspective, it’s important to focus on the analysis of the data and to provide information that will ultimately aid it in some way. When it comes to security, Jim explained that newer Big Data platforms are not built with security in mind. While data is data, many security controls don’t translate to new platforms or scale with the influx of data.

Cloud Computing is Big Data-ready, and price can be compelling, but there are significant security and privacy risks. Robert brought up the argument over public and private Cloud adoption, and said, “It’s not one size fits all.” But can Cloud and Big Data come together? Andras explained that Cloud is not the almighty answer to Big Data. Every organization needs to find the Enterprise Architecture that fits its needs.

The fruits of Big Data can be useful to more than just business intelligence professionals. With the trend of mobility and application development in mind, Chris suggested that developers keep users in mind. Big Data can be used to tell us many different things, but it’s about finding out what is most important and relevant to users in a way that is digestible.

Finally, the panel discussed how Big Data bringing about big changes in almost every aspect of an organization. It is important not to generalize, but customize. Every enterprise needs its own set of architecture to fit its needs. Each organization finds importance in different facets of the data gathered, and security is different at every organization. With all that in mind, the panel agreed that focusing on the analytics is the key.

To view the panel discussion, please watch the broadcasted session here: http://new.livestream.com/opengroup/events/1838807

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Capturing The Open Group Conference in Newport Beach

By The Open Group Conference Team

It is time to announce the winners of the Newport Beach Photo Contest! For those of you who were unable to attend, conference attendees submitted some of their best photos to the contest for a chance to win one free conference pass to one of The Open Group’s global conferences over the next year – a prize valued at more than $1,000/€900 value.

Southern California is known for its palm trees and warm sandy beaches. While Newport Beach is most recognized for its high-end real estate and association with popular television show, “The OC,” enterprise architects invaded the beach and boating town for The Open Group Conference.

The contest ended Friday at noon PDT, and it is time to announce the winners…

Best of The Open Group Conference in Newport Beach - For any photo taken during conference activities

The winner is Henry Franken, BiZZdesign!

 Henry Franken 01 BiZZdesign table

A busy BiZZdesign exhibitor booth

The Real OC Award – For best photo taken in or around Newport Beach

The winner is Andrew Josey, The Open Group!

 Andrew Josey 02

A local harbor in Newport Beach, Calif.

Thank you to all those who participated in this contest – whether it was submitting one of your own photos or voting for your favorites. Please visit The Open Group’s Facebook page to view all of the submissions and conference photos.

We’re always trying to improve our programs, so if you have any feedback regarding the photo contest, please email photo@opengroup.org or leave a comment below. We’ll see you in Sydney!

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