When a data owner's (a business) sensitive data is breached it is difficult to quantify the monetary loss. According to respectable survey sources, the average cost of sensitive data breach for a large size company is about $50,000. I am attempting here to think about this in simple mathametical terms:

There is a data breach. From the data owner's perspective the loss is:

Loss = Cost to protect data + Loss of business due to data theft aka cost of competitive disadvantage

From the data thief's perspective

Net Gain= [Cost of producing the data  *  Data freshness factor] - Cost to steal the data + Profit of business due to data aka gain of competitive advantage

From the above two equations it is very clear that this is not a zero sum game. There is a clear cost asymmetry for a data owner and for a data thief. When there is an asymmetry there is an opportunity. Data owner would not even know that the data is lost because the original copy of the data may be still intact - data thief could have simply copied the data. Data theft does not look like a car theft, there is no vacuum left behind. 

This motivates a data thief to keep the cost to steal low, steal highly valuable data that has a long shelf life and in a way that data owner will never even be aware of theft.

From a data thief's perspective, the cost to steal data if kept high would disincentive him. Moreover, Data freshness factor, i.e. how valuable this data is over period of time plays an important role. A good example is content of today's newspaper is hardly valuable tomorrow, but the content of newspaper two days ahead (if can be procured)would be invaluable. Data relevance is a function of time and other marketplace variables -  Data freshness Factor accounts for that variable. A good way to discourage data thief is to increase his/her cost to steal the data. There are other inferences from the above equation. If there exists no competitive advantage with the stolen data, hardly any thief would even venture to steal the data in the first place. If the cost of producing data is very low, then probably thief can just produce the data himself and would not attempt to steal the data. If the cost of theft is kept high, it would definitely deter the data thief from stealing data using technical mechanisms, then the data thief would exploit weak links in data security such as use of social engineering to get access to the data.

From data owner perspective protecting data becomes very important. How much would the owner be willing to spend? Not definitely the cost equal to cost of producing the data. 1% to 10% of cost of producing data is considered prudent. For a data owner it is difficult to estimate cost of data protection of a specific data, because it is not easy to chunkify data protection costs. Moreover, as Dan Geer says in his book, a data owner has to protect himself from number of intruders not just one.

It pays for a data owner to: be aware of data breaches (or data leaks), employ appropriate mechanisms to protect the data; the cost of protection which is fractional cost of the valuable data and enhance information security awareness of personnel who handle the data.

Data loss is not a zero sum game. The advantage is in favor of a data thief (data thieves rather). Data owner does not give much thought on the value of data unless there is a data theft. But, a data thief has every reason to think about economics of data theft before he acts to steal the data else data thief won't survive in this game and he is very well aware of his advantageous position.

COBIT rivals ITIL from The IT Skeptic

“Everyone is tiptoeing around the fact that COBIT offers a significant competitive body of knowledge (BOK) to ITIL. Sure ITIL goes into more depth in places, but to say COBIT sits over the top is to grossly understate the overlap. COBIT extends a long way down into the “how” and it does it with an intellectual rigour that ITIL lacks.”

Interesting stuff that.  A detailed mapping might help some folks.  Either way, the good news for those keen on understanding risk management is that governance metrics, done right, allow us to understand a part of that “capability to manage risk” we’re always looking for.   Assurance, verification and the acquisition and interpretation of knowledge is king.   Speaking of which….

How To Tell When “Nothing Happens” by Pete Lindstrom

“…problem is that, it isn’t really true that “nothing happens” when you employ some specific security control to prevent an exploit. Not only that, but even when it is difficult to collect data on what didn’t happen, one can devise experiments to tell how frequently that nothing occurred.”

Good analysis is all about the uncertainty.   Speaking of accounting for uncertainty…

Assets Good Until Reached For by Gunnar Peterson

“If you have a 100,000 dekstops or 100,000 servers it hard to manage. You will need to automate and to do that you need to abstract, but you should also realize that its a drawing on a whiteboard not reality. You need abstraction assurance.”

And there’s the trick.  We might call “abstraction assurance” an analog to “confidence” or “uncertainty” in certain priors (metrics) or posteriors (calculated values based on those metrics).  The stronger that abstraction assurance is, the less uncertainty we have in our knowledge and the better our ability to create wisdom from that knowledge (you know, make decisions).

Epstein, Snow and Flake: Three Views of Software Security by Adam Shostack

Adam’s focus is on software security, but the discussion here can be abstracted out into the broader realm of risk management quite nicely.

Two-thirds of firms hit by cybercrime from Security Focus

The US DoJ says that in 2005 (there’s some timely data) 2/3 of their surveyed firms detected at least one cybercrime.  “Cybercrime” is “classified … into cyber attacks, cyber theft, and other incidents.”  Pretty general.  Also from the report:  “Computer viruses made up more than half of all cyber attacks.”

(That sound you hear is me tapping my forehead lightly on large iron object)

Lessons Learned from “Personal” Risk Management By: Christopher Daugherty

“This process is what I call “personal risk management.”  All of us have done it and will continue to do so.  Why is it, then, many companies have ignored following similar principles with the on-going health of the business?  This is a debate with many different answers so I ask you to select the best answer for your employer:

a) Have not ignored as this keeps me awake at night!

b) Please restate the problem, I cannot hear well with my head buried in the sand.

c) We passed our SOX audit so we checked this off the list!

d) We are informed of the challenge but we have a business to run and profits to make

e) Is this what internal audit and risk management has been telling us?”

I’d love to have another blog even more specific - “Ok, that Assurance is Evidence Of What, Exactly?

Today he has a great article called:

What’s the matter with Risk Management?

And “in short, it’s everything.” It pretty much sums up why I had to grow to re-evaluate how our industry does risk, risk management, approaches controls & vulnerability and find a new way.   A couple of things jump out at me in reading Chris’ article:

1.)  Just because that Deming cycle sucks and is full of unknowns doesn’t mean “risk” doesn’t exist, nor that it isn’t of primary importance. Nor does it mean that in the absence of model & methodology, we won’t be “doing” risk analysis anyway - just in an ad hoc method and completely from “the gut”.

Our industry calls these unstructured risk analysis “Best Practices”, as it’s an easy and convenient way of sweeping the unknowns under the rug of bureaucracy and enforcing it via peer pressure.

2.)  What this “suckiness” does mean is that your model and methodology aren’t helping you. As Chris intimates, there is too much uncertainty in the inputs for his model (they are, in the language of Bayesians - too subjective to be useful priors).

Take for example how we might be approaching the “controls” part of our analysis.  Chris writes:

“2. What are the controls that we have to employ?
800-53, ISO 27001, PCI, etc.

Still kinda good, but we basically know that ISO is relatively voluntary and NIST supplies a control catalog and not policies. So here we have to take the control catalog, and mash our policies into it.”

I wouldn’t call this “kinda good” at all :)  These control catalogs only provide a hierarchy within which to look for evidence of  our ability to resist an attacker.  They are incapable of making any claim about the effectiveness of the controls when they are operated at 100% efficiency, or more importantly, what % efficiency our specific organization operates at.

Let’s use Chris Hayes’ Initech as our fictional example.

Initech has a control (a back door on a loading dock).  Now the locks on the door are 100% capable of locking the door.  This is different than saying that they are capable of frustrating all but the top 5% of lockpicking burgalars.  It is also diffferent than saying that in a sample of several “walk around audits” the doors are left open 20% of the time (they are not in compliance with policy 100% of the time).  Even worse, that 80% of the time the door is not propped open?  Yeah, tailgating is a known issue.

So we have several different variables here that we need to account for (and it’s just a door).  But the analogy stands that most “risk management” methodologies are “We have a door, yes/no?” And most GRC platforms, when asked for their “opinion” will simply say “door is needed” or, even worse, “a door policy is needed”.

3.)  Criticality and the Source of Value is all messed up in these Risk Management models.

Chris writes:

Someone wants me to tell them which boxes are more critical than others. This is mainly because of budgetary or operational reasons. To which I usually say “All of them, it is a system after all”.

This literally made me laugh out loud.  And this sort of “rate the firewall as Risk = 500 but rate the actual business application as Risk = 157″ thing is also endemic.  Now Chris is very smart here.  He correctly identifies that the value is tied to the business process the systems support, and not to a specific box.  Oh, we scan at the specific box level - but because of the nature of systemic failures - all the boxes in the process are inexorably interrelated.

One of the reasons I really like FAIR is that the losses are quantified (or qualified) based not on some amorphous value of the box or the process itself, but losses are linked to the actions that the threat will take. Take systems in a highly regulated industries as an example.  Usually the most probable losses aren’t due to system compromise per se, but in the disclosure the compromise causes (regulators are a threat source, after all).  But many “risk management” methodologies will say “online banking is worth $2 billion, the value of the systems is therefore $2 billion”.  And suddenly we’re telling executive management that there’s a 60% probability that they’ll lose $2 billion.

4.)  If the primary source of prior information for your “risk management” methodology is a vulnerability scanner - you’re doing it wrong.  Chris writes:

So we ran a scan and now we have a report. A snapshot in time to make all decisions. Where did these vulnerability ratings come from? Do I even know if my system is at risk? What if I spend my time on vulnerabilities that have no threat?

So first, my thoughts are that actual “vulnerability” must be a comparison of the force a threat can apply, and our ability to resist that force (this is a probability statement, btw).

Changing your thinking about vulnerability now helps us understand the problem in several new ways.  First, you can start to divorce yourself from the scanner.  After all, the scanner is simply providing you with current state information that is usually just relevant variance from policy. It doesn’t really tell you about real “weakness in a system” because the system is an interrelated mess of people, processes and IT assets.

5.)  Finally, most “risk management” approaches just *don’t* do a good job of helping us understand the how’s and why’s of managing risk. In the past, I’ve referred to these standards as really being “issue management” because they are at their heart, an act of discovery - a formal process around gathering prior information.  They are not, in and of themselves, capable of linking the issues discovered to the root cause.  And these root causes?  Yeah, they’re the things that create “risk”.  Not a threat, not a vulnerability, not the existence of an asset - the amount of risk that we have stems from our capability to manage it.

So Chris, I completely agree - but I wouldn’t give up yet.  There actually are a few of us who are focused on what you suggest:

Where to go from here: A fundamental revamp of how to deal with Risk. Where risk professionals focus on the treating the sickness and not the symptoms, and come up with some new success/actionable metrics.

Chris, there’s nothing I want to do more than that.

We are regularly hearing from our security clients about their difficulties finding people with the right skills – or when they do finally find them, these people are too costly to employ because their skills are in such demand.

Indeed, the “unavailability of people with the right skills” was cited as a top challenge for security groups in both our enterprise and SMB surveys.

In comparing need for talent across 25 different IT roles, Forrester analysts came to the conclusion that information security experts are among the hottest roles in IT, sharing the top spot with information/data architects.

The skills shortage is likely to get worse before it gets better. We’re unlikely to see a significant spike in security experts’ salaries to attract those we need to hire: large changes in compensation for senior security personnel would run against the current of economic belt-tightening. Another typical approach to offsetting the shortage would be to train up: foster the career development and advancement of existing security personnel on our payroll. However, with all the outsourcing that is going on – and which will increasingly occur – there is a shrinking pool from which to find people with “the right stuff” worth championing their advancement.

We could look outside of security to others in IT, or even to co-workers in other departments or business groups. But given how poor a job IT Security does of marketing its value proposition, I don’t hold much hope for attracting non-security people.

What do you think? Are we about to hit a very big wall when it comes to skills and staffing? Are you presently feeling the pain of a skills shortage? Do you see such a shortage looming? What measures are you taking to acquire and nurture talent? Which ones are successful and why?

I welcome your thoughts on the topic.