Measuring the Immeasurable: You Have More Data Than You Think You Do

By Jim Hietala, Vice President, Security, The Open Group

According to a recent study by the Ponemon Institute, the average U.S. company experiences more than 100 successful cyber-attacks each year at a cost of $11.6M. By enabling security technologies, those companies can reduce losses by nearly $4M and instituting security governance reduces costs by an average of $1.5M, according to the study.

In light of increasing attacks and security breaches, executives are increasingly asking security and risk professionals to provide analyses of individual company risk and loss estimates. For example, the U.S. healthcare sector has been required by the HIPAA Security rule to perform annual risk assessments for some time now. The recent HITECH Act also added security breach notification and disclosure requirements, increased enforcement in the form of audits and increased penalties in the form of fines. Despite federal requirements, the prospect of measuring risk and doing risk analyses can be a daunting task that leaves even the best of us with a case of “analysis paralysis.”

Many IT experts agree that we are nearing a time where risk analysis is not only becoming the norm, but when those risk figures may well be used to cast blame (or be used as part of a defense in a lawsuit) if and when there are catastrophic security breaches that cost consumers, investors and companies significant losses.

In the past, many companies have been reluctant to perform risk analyses due to the perception that measuring IT security risk is too difficult because it’s intangible. But if IT departments could soon become accountable for breaches, don’t you want to be able to determine your risk and the threats potentially facing your organization?

In his book, How to Measure Anything, father of Applied Information Economics Douglas Hubbard points out that immeasurability is an illusion and that organizations do, in fact, usually have the information they need to create good risk analyses. Part of the misperception of immeasurability stems from a lack of understanding of what measurement is actually meant to be. According to Hubbard, most people, and executives in particular, expect measurement and analysis to produce an “exact” number—as in, “our organization has a 64.5 percent chance of having a denial of service attack next year.”

Hubbard argues that, as risk analysts, we need to look at measurement more like how scientists look at things—measurement is meant to reduce uncertainty—not to produce certainty—about a quantity based on observation.  Proper measurement should not produce an exact number, but rather a range of possibility, as in “our organization has a 30-60 percent chance of having a denial of service attack next year.” Realistic measurement of risk is far more likely when expressed as a probability distribution with a range of outcomes than in terms of one number or one outcome.

The problem that most often produces “analysis paralysis” is not just the question of how to derive those numbers but also how to get to the information that will help produce those numbers. If you’ve been tasked, for instance, with determining the risk of a breach that has never happened to your organization before, perhaps a denial of service attack against your web presence, how can you make an accurate determination about something that hasn’t happened in the past? Where do you get your data to do your analysis? How do you model that analysis?

In an article published in CSO Magazine, Hubbard argues that organizations have far more data than they think they do and they actually need less data than they may believe they do in order to do proper analyses. Hubbard says that IT departments, in particular, have gotten so used to having information stored in databases that they can easily query, they forget there are many other sources to gather data from. Just because something hasn’t happened yet and you haven’t been gathering historical data on it and socking it away in your database doesn’t mean you either don’t have any data or that you can’t find what you need to measure your risk. Even in the age of Big Data, there is plenty of useful data outside of the big database.

You will still need to gather that data. But you just need enough to be able to measure it accurately not necessarily precisely. In our recently published Open Group Risk Assessment Standard (O-RA), this is called calibration of estimates. Calibration provides a method for making good estimates, which are necessary for deriving a measured range of probability for risk. Section 3 of the O-RA standard uses provides a comprehensive look at how best to come up with calibrated estimates, as well as how to determine other risk factors using the FAIR (Factor Analysis of Information Risk) model.

So where do you get your data if it’s not already stored and easily accessible in a database? There are numerous sources you can turn to, both externally and internally. You just have to do the research to find it. For example, even if your company hasn’t experienced a DNS attack, many others have—what was their experience when it happened? This information is out there online—you just need to search for it. Industry reports are another source of information. Verizon publishes its own annual Verizon Data Breach Investigations Report for one. DatalossDB publishes an open data beach incident database that provides information on data loss incidents worldwide. Many vendors publish annual security reports and issue regular security advisories. Security publications and analyst firms such as CSO, Gartner, Forrester or Securosis all have research reports that data can be gleaned from.

Then there’s your internal information. Chances are your IT department has records you can use—they likely count how many laptops are lost or stolen each year. You should also look to the experts within your company to help. Other people can provide a wealth of valuable information for use in your analysis. You can also look to the data you do have on related or similar attacks as a gauge.

Chances are, you already have the data you need or you can easily find it online. Use it.

With the ever-growing list of threats and risks organizations face today, we are fast reaching a time when failing to measure risk will no longer be acceptable—in the boardroom or even by governments.

Jim Hietala, CISSP, GSEC, is the Vice President, Security for The Open Group, where he manages all IT security and risk management programs and standards activities. He participates in the SANS Analyst/Expert program and has also published numerous articles on information security, risk management, and compliance topics in publications including The ISSA Journal, Bank Accounting & Finance, Risk Factor, SC Magazine, and others.

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