Abstract. Describes a decade of experience threat modeling products and services at Microsoft. Describes the current threat modeling methodology used in the Security Development Lifecycle. The methodology is a practical approach, usable by non-experts, centered on data ow diagrams and a threat enumeration technique of 'STRIDE per element.' The paper covers some lessons learned which are likely applicable to other security analysis techniques. The paper closes with some possible questions for academic research.

Richard Stallman - the man that gave us GNU - doesn’t trust Cloud providers with his data and says you shouldn’t either.  Richard believes we should store our private data on our own computers using ‘free’ (as in freedom) software.  The ironic part for Richard is that a significant portion of the Cloud is powered by open source software which he indirectly created (think gcc).

Richard sees it as a question of control.  Control is important but it isn’t the only variable.  Rather, I see it as a question of control, competence and economics.

The quick rebuttal to Richards’ view is this: the average computer user is not as smart as you.  Control is not the same as competence.  Control is about exercising choice, not about requiring everyone in the world to develop sufficient skills to protect complex hardware and software systems (aka their computer) against ever increasing threats.

My view is that privacy is not ‘free’.  It comes at a cost.  Whether you run your own systems or rely on someone else to do it, there is a cost.  There is cost in designing and implementing mechanisms to support privacy.  Beyond upfront costs there are ongoing expenditures to ensure privacy is maintained e.g. maintaining access control lists, testing and applying security patches, data leakage prevention etc.  None of these things are ‘free’.

If we agree that privacy costs money then how much is your privacy worth?

Stop for a second - think of a number…  

Now did we all think of the same number?

The problem with a one size fits all approach to privacy is that we each place a different value on it.

Checking in on the EPIC site, I saw this:  

A new report from Pew Internet and American Life Project indicates that “cloud computing” applications, such as web-based email and other web apps, are raising new privacy concerns. The report Use of Cloud Computing: Applications and Services found that 69% of online Americans use webmail services, store data online, or use software programs such as word processing applications whose functionality is located on the web. At the same time, “users report high levels of concern when presented with scenarios in which companies may put their data to uses of which they may not be aware.” For example, 90% of respondents said that they “would be very concerned if the company at which their data were stored sold it to another party,” 80% say “they would be very concerned if companies used their photos or other data in marketing campaigns,” and 68% of “users of at least one of the six cloud applications say they would be very concerned if companies who provided these services analyzed their information and then displayed ads to them based on their actions.”

What does that tell us?

The average (American) Internet user finds Cloud services convenient but has concerns about how their privacy might be affected by Cloud providers actions (duh!).  The survey identifies a lack of awareness in how private data is used in some consumer based Cloud services (consistent with web advertising awareness surveys).  

Unfortunately, the results of this survey are not very actionable.  The survey doesn’t mention whether these are all ‘free’ Cloud services (we can only assume they are) or ask the respondents what their expectations of privacy are and how much they would be willing to pay for different privacy assurance levels. 

On a sidenote, respondents were not asked if they had actually read the privacy agreement for the services they signed up to.  But the providers know if they did or not…  Or at least, they have the data to figure it out.  At sign up time they can measure the time between displaying the privacy agreement and the user clicking ‘I accept’.  If its just a few seconds then its pretty obvious there was more scrolling than reading going on.  But I think we can probably guess the answer without the data ;-).

I believe we need to be able to link expectation of privacy with cost.

• How much are you willing to pay for privacy?  What level of privacy assurance do you need?
• How much is your Cloud Provider paying to protect your privacy today?  What privacy services could they reasonably offer if they had customers willing to pay?  How might this compare with how you manage your private data on your home computer today?

The cynical view is that we expect privacy but don’t want to pay for it.  Its a bit like uptime - there is a parallel universe out there, where internal IT departments allegedly meet their 99.999% uptime SLAs, but when Gmail goes down, the Sergey Brin witchcraft dolls come out.

From a provider perspective, the “cost” of privacy invariably gets bundled under that line item called ‘Information Security’.  And don’t be fooled, the cost of privacy in reality is more than the salary of the person employed to be the privacy advocate (if there is one).  If we can’t see how much our providers are spending on our privacy then how can we judge if they are spending enough?  And what is enough?  And what can I get if I’m willing to pay a little extra?

Personally, I would rather we get some transparency around privacy costs and assessment of offerings.  However, without a sufficiently sized market of customers willing to pay for privacy assurance and Cloud Providers willing to be more open, I won’t hold my breath.

What about you?  Would you be prepared to pay for privacy?  Should providers be more transparent about what they do and don’t do and how they do it?
 
 

Around the same time that Professor Luckham and his team was working on CEP applications in network management and security management, I was leading efforts to build network and security management control centers for the United States Air Force.  In the beginning, dating back to 1994, my Internet-related work was for Air Combat Command (ACC), working out of ACC headquarters at Langley Air Force Base.

In 1997, I lead a technical team that developed countermeasures against an actual distributed Internet-based attack on the Langley AFB SMTP email infrastructure.  This attack was documented in a technical paper, E-Mail Bombs and Countermeasures: Cyber Attacks on Availability and Brand Integrity, IEEE Network Magazine, Vol. 12, No. 2, pp. 10-17, March/April 1998.  In addition, this attackand countermeasures I designed was featured in Popular Science Magazine in an 1998 article, War.Com and other news channels.  I also published a number of related papers on this topic.

Our team used a rule-based approach for countermeasures against massive email bombs attacks on the Langley Air Force Base email infrastructure.   We called this rule-based system, BombShelter. and it was written in PERL.  I developed both the original software architecture and the original working prototype for BombShelter (in two days) and then we turned the software over to our team who used the rule-based approach for daily attack countermeasures.

I watched for days, and then weeks, as my team designed rules, and the attackers wrote new attacks that circumvented the rules.  Some folks in the Pentagon used to say that I “lead the effort to fight the first war in cyberspace”.   It might have have been the first cyberwar, I am not sure, but it was certainly the first publicly documented cyberwar.  There is no doubt about this.

Without getting into all the historical footnotes and significance of this cyberwar that was fought with experts and rule-based systems, I would like to jump to an important conclusion.

Rule-based systems are useful, but have limited functionality and scaleability in most complex event processing applications.

Rule-based systems are human resource intensive because rule-based systems cannot learn and adapt on their own, humans learn and then write new rules.  This is how rule-based systems work.

This is the motivation behind why I spend a lot of time to search for new, more efficient and adaptive methods as alternatives to rule-based systems.   After extensive research, I published a series of papers on the future of intrusion detection in the Internet.  Intrusion Detection Systems & Multisensor Data Fusion - Creating Cyberspace Situational Awareness [1], helped lead an evolution in Internet security, particularly in the area of network-based intrusion detection systems (IDS).

In my published research work, motivated by limitations with rule-based approaches, I used the same mature functional model that is used to process missile attacks, control global air traffic, and other complex event processing applications in physical space; but I applied these concepts to cyberspace.

Around the same time, Professor Luckham and others were working on similar problems, all related to real-time detection and response to threats in cyberspace.  They were also funded by the US government.

Sidebar: Stream processing of transaction- based systems (databases), another area of interest, was focused on a totally different problem, which was the low latency processing of straight-thru processing in databased-oriented systems.   These stream processing systems were, and remain however,  rule-based systems.  The problems we were trying to solve in cyberspace, however, cannot be efficiently and pragmatically solved by rule-based systems alone.  Only relatively simple scenarios can be efficiently detected by rule-based stream processing systems.

The vast majority of complex event processing classes of problems require rules plus advanced algorithms that can learn and adapt in real-time.    I know this, not from reading papers or taking university classes on rule-bases systems, but from working on some very challenging operational problems in real-time.    This is why I remain interested in complex event processing and why I continue to elaborate on why rule-based systems have limitations.

So can open source weather out the economic storm? Emerging from the dot-com bust, open source has matured, its legal framework and values are established, and serious players are in the game. But as this post on ZDNet points out, consolidation is on the way. “IDC renamed its LinuxWorld Show in San Francisco next year Open Source World – a clear shot across the bow at O’Reilly’s OSCON.” Will open source (from free to lower-cost alternatives to commercial software) flourish in a time of tightening budgets or will projects quietly go away for lack of funding (VC and that pesky business model thing) and, let’s face it, the “extra time” of IT pros tasked yet again to do more with less?

It’s October 2008 and Charles Babcock writes, “CA Embraces Virtualization As Future of Data Center Management”. Beyond keeping up with what competitors are doing, I enjoy this article for the masterful way it depicts the nightmare that is working with traditional frameworks. Too slow, too expensive, too complex, too many modules – it’s all in here. And somehow, I don’t think that was the point of it. So, $154,000 for CA Data Center Automation Manager – which can “consult” the CA CMDB (pricing starting at what do you think, something like $500K to a million – don’t forget those services) plus CA Wily APM (Introscope 8 and Wily Customer Experience Manager 4.2; pricing anyone?) metrics that get fed back into Data Center Automation Manager to help determine the virtual machine resources that are needed. Plus can also integrate info from CA Endeavor’s software change management tracking and CA SysView and in future with CA Management Suite for Mainframe Linux, potentially. I am not kidding about this list. And, we’ve been hearing this for a while – “Unicenter” the brand goes away and is replaced by “CA NSM”. The brand goes away. Why retire a successful brand? Ah.

I love this post on EMC, “Eleven Things You Didn’t Know About the World’s Largest External Disk Storage Company.” Although I guess I really don’t know much about Joe Tucci, since #11 says:

“Contrary to conventional thought, it is not true that the EMC President/CEO is the older, gentler brother of the fictional patriarch of HBO’s hit television series.” Hunh. I just googled him, thinking maybe it was a resemblance thing. Nope."

And on a much lighter note. A funny from Dell. 2 years later, I just stumbled across this Proprietaryville , Jibjab-ish video, called Dell the Journey. Legacy systems being escorted onto the Retirement Home bus. Michael Dell as knight in shining armor, singing no less. Joe Tucci and Larry Ellison showing up as heroes leading the charge against Proprietaryville (yes, funny in and of itself). And my favorite, “Now let’s go kick some proprietary apps.”

The report was written by a committee whose members include William Perry, a professor at Stanford University; Charles Vest, the former president of MIT; W. Earl Boebert, a retired senior scientist at Sandia National Laboratories; Cynthia Dwork of Microsoft Research; R. Gil Kerlikowske, Seattle's police chief; and Daryl Pregibon, a research scientist at Google.

They admit that far more Americans live their lives online, using everything from VoIP phones to Facebook to RFID tags in automobiles, than a decade ago, and the databases created by those activities are tempting targets for federal agencies. And they draw a distinction between subject-based data mining (starting with one individual and looking for connections) compared with pattern-based data mining (looking for anomalous activities that could show illegal activities).

But the authors conclude the type of data mining that government bureaucrats would like to do--perhaps inspired by watching too many episodes of the Fox series 24--can't work. "If it were possible to automatically find the digital tracks of terrorists and automatically monitor only the communications of terrorists, public policy choices in this domain would be much simpler. But it is not possible to do so."

A summary of the recommendations:

• U.S. government agencies should be required to follow a systematic process to evaluate the effectiveness, lawfulness, and consistency with U.S. values of every information-based program, whether classified or unclassified, for detecting and countering terrorists before it can be deployed, and periodically thereafter.

• Periodically after a program has been operationally deployed, and in particular before a program enters a new phase in its life cycle, policy makers should (carefully review) the program before allowing it to continue operations or to proceed to the next phase.

• To protect the privacy of innocent people, the research and development of any information-based counterterrorism program should be conducted with synthetic population data... At all stages of a phased deployment, data about individuals should be rigorously subjected to the full safeguards of the framework.

• Any information-based counterterrorism program of the U.S. government should be subjected to robust, independent oversight of the operations of that program, a part of which would entail a practice of using the same data mining technologies to "mine the miners and track the trackers."

• Counterterrorism programs should provide meaningful redress to any individuals inappropriately harmed by their operation.

• The U.S. government should periodically review the nation's laws, policies, and procedures that protect individuals' private information for relevance and effectiveness in light of changing technologies and circumstances. In particular, Congress should re-examine existing law to consider how privacy should be protected in the context of information-based programs (e.g., data mining) for counterterrorism.

Here are more news articles on the report. I explained why data mining wouldn't find terrorists back in 2005.