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Schneier on incident response

By Jake Edge
September 24, 2014

AppSec USA

Bruce Schneier is a cryptographer and security specialist who is well-known in computer circles even though he has often branched into more general security areas in recent years. His blog is a great source of security news (and, of "quotes of the week" for this page, as readers know). Beyond all that, he travels to many security conferences to give talks, which is just what he did at AppSec USA in Denver on September 18. The keynote topic was "incident response" (IR), which is an area that is finally getting more attention in the security-product space, he said.

Interestingly, Schneier's talk didn't really dwell all that much on IR. Instead, he looked at some trends that are changing the industry, along with some economic principles that are relevant to the computer security market. Along the way, he also described a feedback loop that is used by the US Air Force (USAF) and how it relates to network attacks and the response to them.

Three trends

[Bruce Schneier]

There are three trends that are currently important to the security industry, he said. The first is that we are "losing control of our infrastructure", which is the result of two separate things. The rise of cloud computing "means we no longer have control of our data". Schneier uses Eudora for his email, "but I am a freak". His company (he is the CTO at Co3 Systems, which makes IR tools, as he disclosed near the end of the talk), however, outsources its email to Google.

Moving data to the cloud means that we cannot affect the security of the system any longer, he said. You can't ask Google for more security on your email storage, you just get what they provide. You also have no idea where the actual physical bits of your data reside; they could be anywhere in the world.

We are also accessing our data with devices that we have less control over, which is also a loss of infrastructure control. Mobile devices are often locked down, such that we can't even wipe their memory and storage because there is no access at that level. There are lots of good reasons for locking down devices in that manner, but it does affect security. The business case for companies like Apple and Microsoft to control these devices is quite strong, to the point that Schneier expects to see phone and desktop operating systems converge—to somewhere that is much closer to the "less user control" phone side of that continuum.

The second major trend is that attacks are getting more sophisticated, as we have seen over the last few years. There is a lot of "cyberwar" rhetoric and there is clearly an increase in the capabilities of attackers. He doesn't really like the term "cyberwar", since we are not actually fighting a war in cyberspace, but there are parallels between actual warfare and the internet-based attacks occurring today.

In real wars, you can generally determine who the attacker is by the weaponry used—a tank means a government, since no one else can afford them. In computer attacks, that is not true: everyone is using the same weapons.

You can place attackers on a two-axis graph, where the axes are "skill" and "focus", Schneier said. Script kiddies are clearly low skill, low focus, while attacks like that against Target are from high-skill, low-focus attackers—they didn't want Target's customers' credit card information, they just wanted credit card data. In that case, relative security matters. Since Target was not as well-secured as its "neighbors", it was attacked.

But high-skill, high-focus attacks, like advanced persistent threats (APTs), make for a completely different threat model. APTs are personal for some reason; the attacker wants to get at a particular target. Protecting against that kind of attack comes down to absolute security: is the attacker better than the defender?

As it turns out, we know the answer to that question: yes. When penetration testers attempt to get into a system or network, they essentially always do, he said. We do not know how to defend against targeted attacks. In the history of warfare, as weapons and defenses have evolved, sometimes the attacker has had the advantage and sometimes it has been the defender. On the internet right now, the attacker has the advantage and will for the foreseeable future, Schneier said.

The final trend that he noted was the increasing government involvement in cyberspace. It goes beyond the NSA and other secret services spying on internet activity. There is a "complicated regulatory environment", which means that there is a lot of "legal stuff that organizations have to know and follow". Businesses and other organizations tend to be collateral damage when governments act on the internet—to censor it, conduct espionage on it, or attack adversaries using it. All of that is only going to get worse, he said.

Economics

Schneier then moved into some economic principles that are important to consider when looking at the market of computer-security products. First, network effects are crucial to the success of a product. He cited Metcalfe's law (the value of a network is proportional to the square of the number of connected users) to explain how network effects work for things like SMS, Skype, and Facebook. It is also important to the battle between iOS and Android, or between Mac OS X and Windows. The "big get bigger" due to network effects; Facebook gets bigger because you are going to join the network where your friends are, not the network that is better.

Another important economic concept is fixed vs. marginal costs. For physical products, much of the cost is in marginal costs, whereas in software it is almost all in fixed costs. Creating the first copy of a program costs a lot, but each copy after that costs little to produce. Books are similar, he said. Some printing company could (illegally) start producing copies of his books and sell them for a few dollars, since they would not have to recover the fixed cost by paying him royalties. He could retaliate by temporarily dropping the cost of his book below that of the "competitor", to drive them out of business—which is the tactic that Walmart employs against its local competition, he said.

"Switching costs" is yet another principle that comes into play. It is much more expensive to switch cell phone providers than it is to switch cola brands. He cited Shapiro and Varian's "fundamental theorem" that the total value of a software company is the cumulative cost for its customers to switch to a competitor. In effect, "the higher the switching costs, the more the company can piss you off", he said. AT&T just has to "not suck", while a cola has to be better in some measure.

Another example of high switching costs is trying to move from iTunes to something else: "good luck taking your music" with you. The same goes for trying to move from a Kindle to a Nook (or vice versa). Cell-phone-number portability is an effort to lower switching costs, since a user can switch without having to update all of their contacts, print new business cards, and so on.

The "lemons market" is an idea by George Akerlof that won him the Nobel Prize in Economics. It concerns markets where sellers know a lot more than buyers (i.e. asymmetric markets). In those markets, "bad products drive good products out of the market". If the buyer cannot tell the difference between a good and a bad product, they will buy the bad because it is cheaper, he said. If there are two encryption products on the market, both with the same algorithms, but one is implemented well and the other not, buyers will buy the cheaper one.

This is why "signals" are important. Things like certifications and "those really dumb awards at conferences" are useful. Those are signals that allow the buyers to convince themselves they are buying a "not bad" product. The old adage that "no one ever got fired for buying IBM" is another kind of signal.

The final economic principle Schneier mentioned is "prospect theory", which came from two psychologists. They are the only non-economists to win the Nobel Prize in Economics and they did so by "telling economists that everything they believe is wrong", Schneier said with a chuckle. Unlike previous models, prospect theory shows that humans are risk-averse when it comes to losses, and risk-seeking when it comes to gains.

[Bruce Schneier]

This behavior is also observed in other primates, Schneier said. The best explanation he has heard comes from evolutionary biology. If you consider a species on the edge of extinction, even a small loss means they are dead. If they can avoid any chance of that loss, they are better off. But a small gain is worth seeking because it will improve the chances to live to see another day.

That theory explains why it is difficult to sell cybersecurity. It is the same with insurance or burglar alarms, he said. If you go to your boss to say you need something to secure the network, he is likely to point out that you didn't have it last month and the network ran just fine. It is not impossible to sell cybersecurity, but it does require fighting against this basic psychological principle.

Response

In computer security, there is a need for response, because both prevention and detection are imperfect. He used to say that security is a process, not a product, but that was a "strategic idea". If you look at it more tactically, security is both a process and a product. He now talks about "people, process, and technology".

But there is a general idea that people can't help with security. There is a focus on automation for tasks like threat detection and system updates. However, response cannot be fully automated because it requires people to understand and react to what is happening. All attacks are different, the networks are different, the regulatory environments are different, and on and on. Those things are not necessarily different in technical ways, either; they are different in "people ways".

All of that means the people-to-technology ratio goes up for response. If you look at real-world emergency response (e.g. police and firefighters), it is similar. And, like with those organizations, security response needs technology that supports people, rather than replacing them.

That's where the USAF's feedback loop comes into play. An observe-orient-decide-act (OODA) loop is what pilots repeatedly use during a dogfight. If you can perform that loop faster than your opponent, you will win the fight. The USAF uses the OODA loop to evaluate technology—it wants technology that supports the pilot in handling one of those four functions.

The same OODA loop is present in incident response, Schneier said. The speed of handling that loop is crucial. Being faster than the attacker means getting them out of your system. So the security industry needs tools to facilitate the OODA loop.

That means better tools to observe what is happening (observe) and to fill in the context from the outside world (orient), which would provide information like the presence of new malware observed in the wild, an upheaval in some country, or that the company is going through a merger. Tools to help with the decision-making process are needed as well (decide), which is an area that needs a lot more work, he said. Who gets to decide, and how those decisions are audited after the fact, are two important pieces of the puzzle. Finally, there is a need for tools to help take the decision and make it happen (act). All those areas are ripe for new tools and we are starting to see them, he said.

For the security industry, the 1990s were the decade of protection, while the 2000s were the decade of detection. This decade will be the decade of response. But, unlike protection and detection tools, response tools will not suffer the same fate—bad products pushing out the good. Because response tools will be people-oriented, the good products will beat out the bad. Incident response tools and products will change the industry, Schneier concluded.


Index entries for this article
SecurityIncident response
SecurityKeynotes
ConferenceAppSec USA/2014


to post comments

Schneier on incident response

Posted Sep 25, 2014 4:17 UTC (Thu) by euske (guest, #9300) [Link]

I understand there's a marketing aspect in this talk, but overall I found this article very refreshing and insightful. Thanks for posting.

Schneier on incident response

Posted Sep 25, 2014 5:08 UTC (Thu) by raven667 (guest, #5198) [Link] (2 responses)

The term OODA loop comes from Col. John Boyd who was a strategist and reformer in the USAF, his Wikipedia page goes in more detail. You can see an application of these principals not just in conflict but more generally in Agile/Scrum development methodology where the strategy is to re-evaluate and iterate faster. In conflict, such as with security, having better visibility and making decisions faster not only means keeping one step ahead of your opponent but that your opponents decisions will make less sense and be more in error as their observations become unglued and delayed from the reality of their situation. I think in computer security though this kind of thing favors the attackers again, most defenders are reacting to things like monitoring alerts or log reports which have significant time delay whereas an attacker might have an interactive shell and can afford to back out at the first sign of trouble.

Schneier on incident response

Posted Sep 26, 2014 8:22 UTC (Fri) by jezuch (subscriber, #52988) [Link]

> I think in computer security though this kind of thing favors the attackers again, most defenders are reacting to things like monitoring alerts or log reports which have significant time delay

Huh, for some reason it reminded me of the Three Mile Island incident, where the alerts were delayed by a slow printer, with quite disastrous results. Maybe if you consider the nuclear reactor to be the "attacker" and the operators as "defenders"... ;)

Schneier on incident response

Posted Sep 26, 2014 17:03 UTC (Fri) by Baylink (guest, #755) [Link]

In at least one of his novels, Tom Clancy gets right inside the OODA loop, writing 3PLO in the mind of a fighter pilot in combat. I *think* that makes it Red Storm, but I'm not sure.

Schneier on incident response

Posted Sep 26, 2014 3:28 UTC (Fri) by zblaxell (subscriber, #26385) [Link]

25 years ago, the most secure systems were the ones where suitably authorized agents (usually their owners) could inspect everything the machines were doing, and intervene if they weren't doing something correctly. Security came from enumerating everything that is happening and confirming that the list of all happening things contains zero successful attacks (hey, the NSA does it, it must work. ;)

25 years later, nothing has changed, and inspection and intervention (the O and A of OODA) are more important than ever--yet modern mobile devices are going out of their way to do the exact opposite of the secure thing. End-users who want to implement an OODA loop must first attack and defeat their own device manufacturers, then try to keep their devices secure while the entire world fights back.

I'm stuck with mid-2000's mobile technology because the newer stuff is not better and the older stuff isn't mobile. :-/

Schneier on incident response

Posted Sep 26, 2014 17:44 UTC (Fri) by terber (subscriber, #3311) [Link] (1 responses)

"prospect theory", which came from two psychologists. They are the only non-economists to win the Nobel Prize in Economics

That were Daniel Kahneman and Amos Tversky. Kahneman won the Nobel prize in 2002, but at that time Tversky was unfortunately already dead for six years, so the second sentence should be changed accordingly.

Schneier on incident response

Posted Sep 26, 2014 23:52 UTC (Fri) by rschroev (subscriber, #4164) [Link]

In addition, Kahneman and Tversky are not the only non-economists to win the Nobel Prize in Economics: John Forbes Nash has won it too, and he was a mathematician. IIRC he was surprised to learn that his theory was used in economics.

Prospect Theory

Posted Sep 26, 2014 21:06 UTC (Fri) by brugolsky (guest, #28) [Link] (8 responses)

Unlike previous models, prospect theory shows that humans are risk-averse when it comes to losses, and risk-seeking when it comes to gains.

Prospect theory is a bit more involved than that; in particular, the probability and magnitude of the gains and losses matter, as well as intertemporality (which relates to survivorship). More fundamental is the "reflective" symmetry between losses and gains: whatever I'd do with gains, I'll likely do the opposite with losses.

In a blog post from 2008, Bruce frames this statement in exactly the opposite way, which is more relevant for the argument that he is making:

People tend to be risk-averse when it comes to gains, and risk-seeking when it comes to losses.

He goes on to say:

Security is a fear sell. It's a choice between a small sure loss -- the cost of the security product -- and a large risky loss -- the potential results of an attack on a network.

In an earlier blog post, he does a better job of enumerating the actual factors:

There are several specific aspects of the security trade-off that can go wrong. For example:
  • The severity of the risk.
  • The probability of the risk.
  • The magnitude of the costs.
  • How effective the countermeasure is at mitigating the risk.
  • How well disparate risks and costs can be compared.
The more your perception diverges from reality in any of these five aspects, the more your perceived trade-off won't match the actual trade-off. If you think that the risk is greater than it really is, you're going to overspend on mitigating that risk. If you think the risk is real but only affects other people--for whatever reason--you're going to underspend. If you overestimate the costs of a countermeasure, you're less likely to apply it when you should, and if you overestimate how effective a countermeasure is, you're more likely to apply it when you shouldn't. If you incorrectly evaluate the trade-off, you won't accurately balance the costs and benefits.

So in brief: (1) security has real costs in both money and attention, (2) managers often underestimate the risk of a security incident, and (3) a manager's (short-term) interests (and evaluation metrics) are not necessarily coincident with the (long-term) interests of the organization, shareholders, and customers.

Prospect Theory

Posted Sep 26, 2014 21:30 UTC (Fri) by raven667 (guest, #5198) [Link] (7 responses)

That reminds me very much of a presentation by Chris Cronan of Halock Labs on how to score and manage risk in a compliance environment (HIPPA, PCI, FISMA, etc.) where risk = likelihood x impact where those are on a scale of 1-5 and you set a threshold for acceptable risk at say 8, based on your organizations tolerance for risk and agreed upon standards for likelihood and impact scores.

If you can quantify and sort the issues you find you can get a handle on really fixing the most important things rather than be driven by unthinking fear, or sounding like some TV Hacker.

http://www.halock.com/blog/author/ccronin/
http://www.cio.wisc.edu/Cronin-RiskSecurityCompliance_-_C...

Prospect Theory

Posted Sep 26, 2014 23:41 UTC (Fri) by dlang (guest, #313) [Link] (6 responses)

The problem with this approach is in trying to quantify the risk. There are a lot of things that can happen, which are more likely than others varies over time (what gets publicity, what tools do the script kiddies have, who is targeting you, etc)

If you try to evaluate everything on a scale of 1-5, you end up with a lot of low-risk items being considered equivalent.

It's a good idea in theory, but in practice it doesn't help much.

Prospect Theory

Posted Sep 27, 2014 2:04 UTC (Sat) by raven667 (guest, #5198) [Link] (5 responses)

In practice you have a limited budget of time and money so being able to prioritize your security spending based on risk is of value, especially in a large organization where the person approving the expenditure of resources is not likely to have any real understanding of what they are approving.

Prospect Theory

Posted Sep 27, 2014 2:17 UTC (Sat) by dlang (guest, #313) [Link] (4 responses)

I absolutely agree with you on the need to prioritize spending.

I'm just saying that evaluating the risk on a scale of 1-5 really doesn't help much. There are too many possible problems and the probability that they will be exploited and the result of that exploit are not known well enough to reduce it to a simple number.

You can reduce it to a number, but in doing so, the person producing the number is really the one making the decision. If they decide that it was a high risk the "decision maker" will approve it, if they decide it's a low risk the "decision maker" will not approve it.

So this approach is great for justifying things, but poor for actually deciding things.

Prospect Theory

Posted Sep 27, 2014 2:55 UTC (Sat) by raven667 (guest, #5198) [Link] (3 responses)

But you aren't setting the score for the risk, that't the product, you are scoring on likelihood, which is maybe the most subjective, and impact which is easier to quantify. You are right in that the person assessing the likelihood could just make stuff up and corrupt the process but the impact is something that should have more collaboration with the business people and can be much more quantitative. If you evaluate honestly, and don't just try to screw the finance department into buying you the new shiny security toy, then you might find some benefit otherwise GIGO.

This isn't about correctly guessing that next week someone is going to find a critical bug in bash that turns your world upside down, even with HIPPA you aren't held to that kind of standard, reasonable and prudent measures, which are highly subjective, are the standard, this is about constraining your problem space in a general way so that you aren't spasticly trying to fix all the possible problems, wasting weeks and months of effort on minutia that doesn't matter, driving yourself insane with stress while doing it.

Even after all your effort, someone might still break into your stuff, that's just the risk you take being on the Internet.

Prospect Theory

Posted Sep 27, 2014 4:35 UTC (Sat) by dlang (guest, #313) [Link] (2 responses)

The problem is that for a very large percentage or issues, the likelihood is what determines the risk.

The Impact of the risk can always end up being "your systems or 0wned" (see the recent example of a 1 byte overflow that Google programmers used to get total control of a system)

so everything boils down to guessing right on the likelihood of the risk to generate the resulting risk.

Or, if you are trying to guess the impact of an unknown exploit, you now have two randomly picked numbers that you are multiplying together to evaluate the risk.

It's not that hard to look at several items and rank them in what you think is the order of likelihood and impact, where you fail is when you try to quantify that issue A is 4x as likely as issue B

Prospect Theory

Posted Sep 27, 2014 17:44 UTC (Sat) by raven667 (guest, #5198) [Link] (1 responses)

As I said before, the likelihood is the most subjective number, but you aren't held to the impossible standard of accurately predicting the future, only that you make a reasonable effort, so you aren't expected to predict Shellshock and that kind of likelihood would probably rank low. What's the likelihood of a laptop getting stolen, or an unforseen 0-day or a bug in your internal web app (which depends on what kind of security practices your developers engage in).

Having your systems get owned is part of the impact but it isn't the whole impact in itself, what's more important is what happens if a particular system gets owned, does the application have access to personally identifiable information, what's the cost if that gets exposed. There is a difference between spending time to do incident response, wipe and reinstall (low impact) and business-ending legal action (severe impact).

These values may be subjective but they aren't random, you set up guidelines on how you score based on what is important to your organization. The scores can also help focus effort and let you know what good enough is so you can stop trying to be perfect and move on to the next need.

Prospect Theory

Posted Oct 5, 2014 18:55 UTC (Sun) by Wol (subscriber, #4433) [Link]

When I first saw this, saying to score the risk, and the impact, on scores of 1-5, it was pointed out that for high risk/high impact threat, it had the same effect whether you reduced the risk, or the impact. My immediate reaction was that you would get a far better crude approximation by multiplying the risk by the impact squared.

After all, doesn't it stand to reason :-) that reducing the *impact* of a breach is a far better (and more easily quantifiable) use of scarce resources than trying to reduce the risk of a breach.

Cheers,
Wol


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