Jack Jones has more than nine years experience as a Chief Information Security Officer (CISO), and is the inventor of the Factor Analysis Information Risk (FAIR)framework. Jack Freund has more than 14 years in enterprise IT experience, is a visiting professor at DeVry University, and chairs a risk-management subcommittee for ISACA.
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?
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.
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: What parts of organizations aren’t being assessed for risk and should be?
Freund: The big problem 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.
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 Factor Analysis Information Risk (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: 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?
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.
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: 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?
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.
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: 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: What's the future of risk management, and what does the cloud trend 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 the Factor Analysis Information Risk (FAIR)framework. 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.
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.
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.
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 the Factor Analysis Information Risk (FAIR)framework, but without some sort of framework like that, there's no way you can get there.