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?
 
 

Because then you get a Maginot Line problem. [After World War I, the French erected concrete fortifications to prevent Germany from invading again -- a response to the previous war, which proved ineffective for the next one.] You know, they make sure they solve that particular problem, the Germans will not invade from here. The thing you have to be aware of most obviously is scenario planning, because typically if you talk about scenarios, you'll overestimate the probability of these scenarios. If you examine them at the expense of those you don't examine, sometimes it has left a lot of people worse off, so scenario planning can be bad. I'll just take my track record. Those who did scenario planning have not fared better than those who did not do scenario planning. A lot of people have done some kind of "make-sense" type measures, and that has made them more vulnerable because they give the illusion of having done your job. This is the problem with risk management. I always come back to a classical question. Don't give a fool the illusion of risk management. Don't ask someone to guess the number of dentists in Manhattan after asking him the last four digits of his Social Security number. The numbers will always be correlated. I actually did some work on risk management, to show how stupid we are when it comes to risk.

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.

Blogger: Dan Blum

With the crisis in financial markets still unfolding, it is important to draw what lessons we can from the experience. Since the roots of the crisis lie in a monumental failure of risk management, it’s important to understand more about what happened, and then draw some parallels to our business risk management and  IT risk management situations.

The risk management failure in the housing market and on Wall Street had multiple interdependent dimensions:

• Mortgage lenders abandoned long standing prudent loan practices. They made too many loans that buyers might not be able to repay. Exotic instruments like ARMs, option ARMs, and interest only loans proliferated. In many cases, all pretense of lending standards were abandoned, so-called “liar loans” approved.
• Capital was grossly over-leveraged. Mortgage lenders and other financial services packaged loans into securities, which they sold to raise capital to support more lending. Real capital reserve requirements to back loans were reduced. Of course, if borrowers could not repay loans, all or parts of the derivative securities would become worthless.
• Risk was aggregated at Fannie Mae, Freddie Mac, and mortgage loan insurance companies. These companies bought or insured some mortgage loans, providing something of a backstop should loans fail. Government sponsored enterprises (GSEs) Fannie and Freddie in turn became over-leveraged and securities that they sold were in turn repackaged in the murky brew of mortgage-backed securities called collateralized debt obligations (CDOs) and other exotic instruments returning generous yields.
• Non-Caveat Emptor. Institutional wealth funds and financial services firms who should have known better bought securities that had been deliberately structured to obfuscate risk. They bought securities they didn’t understand with buried tranches of toxic subprime loans..

It was a great Ponzi scheme – one that kept working as long as housing prices were going up; the recipients of subprime loans could always flip that house to the next buyer. Everyone made money. As Chuck Prince of Citigroup famously put it during a July, 2007 interview: “So long as the music is playing, you’ve got to keep dancing. We’re still dancing.” But one month later, the music stopped. Since then, Citigroup and other financial institutions have taken massive writeoffs with more to come. Wall Street titans like Bear Sterns, Lehman Brothers, Merrill Lynch, and AIG have fallen or been bought out.

What can we learn from this risk management debacle?

As business risk managers and investors, we should ask questions like these:

• Does the executive incentive structure of the company encourage managers to dance around risk? Many Wall Street firms paid senior managers 5 times their salary in bonuses tied to annual growth alone.
• Is the company over-leveraged? Is it borrowing too much money and betting it on ventures with uncertain outcomes?
• Are financial models used for risk management realistic? Earlier, I described the mortgage market of the past few years as a Ponzi scheme, where risk management models must have assumed prices would keep rising. Unlike the dotcom boom whose demise many predicted, very few in the industry foresaw the sharp declines to come in housing prices and sales volumes. Historically, the U.S. housing market has been a steadily rising one, but on the other hand the 2000s saw unprecedented rates of price increases. In reality, what goes up must come down.
• Has your company’s risk council ever performed worst case scenario analysis and built adequate reserves? In the days before economics emerged as a would-be “hard” deterministic science, business leaders may have been more cautious, more aware of and more accepting of uncertainty. Events like the Great Tulip Bubble came once in decades or centuries – not every few years. Note that legendary investor George Soros has proposed a Theory of Reflexivity that, if true, helps explain the recent extremes of boom and bust cycles. This theory holds that market participants model market behaviors based on self-interest, and for a time, their manipulations change the reality of the market – until gravitational forces bring it back to earth. Has the music of ephemeral success played to the backbeat of deterministic-sounding economic models gone to your heads and infected your risk management models?
• Are cost cutting efforts pursued blindly? Outsourcing and other forays into treacherous global waters may be giving away the crown jewels. Smart companies cut costs, but they do it in smart ways. Smart companies think like intelligence agencies as they parcel out work to different partners with varying levels of dependability, and they check on those partners.

Risk management failures can also occur at the more technical level of IT security. As IT risk managers, we might ask questions like these:

• Are the accounting and financial systems your IT department supports under adequate control? As Fred Cohen wrote in one of our documents: “Many companies use computers to manage financial systems, and despite the Sarbanes-Oxley Act (SOX) claims about accounts being properly kept, there are many attacks on financial systems that remain. For example, most of the largest financial systems in the world running on common financial databases do not use double-entry bookkeeping and are thus susceptible to all manner of frauds by insiders.” We find it troubling that a prudent control dating back to the 12th century is going out of style in the name of convenience and cost cutting. Kind of like credit checking became anachronistic during the housing bubble, eh?
• Is the “separation” in your “separation of duty” (SoD) for real? Sure the SOX auditors are looking for SoD, and maybe you have different administrators with different accounts maintaining different systems or functions. But when they say Western civilization may be but one weak password from collapse they’re not lying. Look what happened to Sarah Palin’s email account! Weak and straggly SoD is a problem across all critical IT systems where deperimiterization and server consolidation may be bringing down protective barriers, identity management is weak, and strong process controls (e.g., where two people must sign on, one perform a critical operation such as backbone router reconfiguration, and the second observe) abandoned in the name of expediency.
• Are risks being aggregated to unacceptable levels in centralized control systems? There are many ways that risks aggregate within enterprise IT infrastructures as we pursue automation and cost cutting. Network risks aggregate when centralized domain name system control is implemented. Application risks aggregate when common infrastructure is shared among applications. And enterprises aggregate platform risks when they use low-assurance endpoints, authentication, and directory systems with single sign-on to access large numbers of resources and don’t separate high consequence systems.
• Non-caveat emptor: Has IT security really done the worst case consequence analysis, attack graphs, and vulnerability analysis to know when putting more eggs in a supposedly stronger basket aggregates risks to an unacceptable level? Or are you depending only on vendor claims about some black box appliance equivalent of a risk-obfuscated CDO security? Caveat emptor (buyer beware) again! (The good news is we’ll keep talking about promoting vendor and product rating systems so you don’t have to do all the detailed product analysis yourself, but that’s another post.)

There are many parallels between the monumental risk management failure in the financial markets, and the probable weaknesses in our day to day business risk management and IT risk management. Abandonment of prudent practices for profit; excessive leverage and centralization; ill-constructed risk analysis models; risk obfuscation; and a failure of caveat emptor seem to be common problems. Please take this as a wakeup call to sharpen up the risk management thinking, process, and execution.

Introduction

Virtualization is a word used by consumers and also by IT. But, do we all mean the same thing?

A very cool video from Cisco provided answers to “what is virtualization” from an  engineering perspective, data center perspective, IT perspective and the user perspective (virtual world).

Virtualization is about breaking the bonds between applications and server hardware, nodes and networks, applications and operating systems.

Why is this interesting? Virtualization holds the promise to transform the way we work, live, learn and play.

Why virtualize?

The real estate boom over the last 30 years has driven people to the suburbs. People didn’t mind commuting for an hour with lower gas prices. Today, we have a weak economy and gas prices are high. Something has to change.

Many are opting to stay at home. Businesses are trying out telecommuting, some (like Cisco) are even offering telepresence. This helps by reducing carbon footprint. Corporations are breaking free from physical requirements. The global workforce is also having an impact on the network. These changes are having a huge impact on the network.

We are on the cusp of transitioning from virtualization to VIRTUALIZATION.

“One to many….many to one.”

This is Cisco’s idea of virtualization.

Consider the different roles we play in life - one to many. Spouse, executive, friend, parent, gym rat. This would be “one to many”. This is exactly what virtualization does. It allows you to partition resources off that you can use on the fly.

Where do I start?

Virtualization starts with server and storage. But, it’s the network that touches everything - it spans the physical, the virtual, and the cloud. This provides the connectivity to all these resources. The network brings transparency to the picture. It allows you to better monitor performance and better implement security - great benefits!

Why do I need this?

At Cisco, we saw that we were only using 20% of our storage utilization. We wanted to virtualize our datacenters. When we did that, we were able to get 68% storage utilization. For each year that we were able to defer buildup, we saved $40 million.

From a business standpoint, virtualization helps you differentiate and work faster. Provisioning in minutes, improved productivity and competitive differentiation, using less power (environmental impact), and up the ante of business continuity. If VMWare fails? It’s OK. You can reprovision it on the fly.

Is it for everyone?

IT organizations tend to be siloed. You have the IT side and the Operations side. Each has responsibility. For virtualization to work, these walls have to come down. The concept of virtualization depends on shared resources.

Metcalfe’s Law of the Network Effect

Everytime you add a node to the network, you increase the value. This is what happens with virtualization. Every device you virtualize increases the power of each device. More control of environment and more efficiency.

This leads to…

Cloud computing.

Wow, show of hands from the audience when Marie asked “how many are using cloud computing?” and “how many are using your own clouds?” - not a lot of hands were raised. Interesting considering the coverage cloud computing has and the focus of it.

Cloud computing has three possibilities at Cisco:

• Flexible infrastructure (hosting)
• Abstract services (APIs)
• Application services (SaaS)

Automation is going to be key, and will need to integrate virtualization-aware elements.

Can you imagine if you wanted interoperability in the cloud? People haven’t even begun thinking about it.

Conclusion

As you virtualize, your role will change. You will think more about strategy. But keep in mind these “minefields” of virtualization:

• Insufficient planning
• Lack of standards
• Weak security

Security cannot be an afterthought. It has to be planned. We’ve seen new forms of malware, hypervisor attacks, and root kit infections.

As higher expectations from end users evolve, we’re becoming not server oriented, but SERVICE oriented.

Tips:

• Think holistically
• Consider IT culture - equipment and people