Category errors in (information) security: how logic can help

(Information) security can, pretty strongly arguably, be defined as being the process by which it is ensured that just the right agents have just the right access to just the right (information) resources at just the right time. Of course, one can refine this rather pithy definition somewhat, and apply tailored versions of it to one’s favourite applications and scenarios.

A convenient taxonomy for information security is determined by the concepts of confidentiality, integrity, and availability, or CIA; informally:

the property that just the right agents have access to specified information or systems;
the property that specified information or systems are as they should be;
the property that specified information or systems can be accessed or used when required.

Alternatives to confidentiality, integrity, and availability are sensitivity and criticality, in which sensitivity amounts to confidentiality together with some aspects of integrity and criticality amounts to availability together with some aspects of integrity.

But the key point about these categories of phenomena is that they are declarative; that is, they provide a statement of what is required. For example, that all documents marked ‘company private’ be accessible only to the company’s employees (confidentiality), or that all passengers on the aircraft be free of weapons (integrity), or that the company’s servers be up and running 99.99% of the time (availability).

It’s all very well stating, declaratively, one’s security objectives, but how are they to be achieved? Declarative concepts should not be confused with operational concepts; that is, ones that describe how something is done. For example, passwords and encryption are used to ensure that documents remain confidential, or security searches ensure that passengers do not carry weapons onto an aircraft, or RAID servers are employed to ensure adequate system availability. So, along with each declarative aim there is a collection of operational tools that can be used to achieve it.

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Just how sophisticated will card fraud techniques become?

In late 2009, my colleagues and I discovered a serious vulnerability in EMV, the most widely used standard for smart card payments, known as “Chip and PIN” in the UK. We showed that it was possible for criminals to use a stolen credit or debit card without knowing the PIN, by tricking the terminal into thinking that any PIN is correct. We gave the banking industry advance notice of our discovery in early December 2009, to give them time to fix the problem before we published our research. After this period expired (two months, in this case) we published our paper as well explaining our results to the public on BBC Newsnight. We demonstrated that this vulnerability was real using a proof-of-concept system built from equipment we had available (off-the shelf laptop and card reader, FPGA development board, and hand-made card emulator).

No-PIN vulnerability demonstration

After the programme aired, the response from the banking industry dismissed the possibility that the vulnerability would be successfully exploited by criminals. The banking trade body, the UK Cards Association, said:

“We believe that this complicated method will never present a real threat to our customers’ cards. … Neither the banking industry nor the police have any evidence of criminals having the capability to deploy such sophisticated attacks.”

Similarly, EMVCo, who develop the EMV standards said:

“It is EMVCo’s view that when the full payment process is taken into account, suitable countermeasures to the attack described in the recent Cambridge Report are already available.”

It was therefore interesting to see that in May 2011, criminals were caught having stolen cards in France then exploiting a variant of this vulnerability to buy over €500,000 worth of goods in Belgium (which were then re-sold). At the time, not many details were available, but it seemed that the techniques the criminals used were much more sophisticated than our proof-of-concept demonstration.

We now know more about what actually happened, as well as the banks’ response, thanks to a paper by the researchers who performed the forensic analysis that formed part of the criminal investigation of this case. It shows just how sophisticated criminals could be, given sufficient motivation, contrary to the expectations in the original banking industry response.

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Mathematical Modelling in the Two Cultures

Models, mostly based on mathematics of one kind or another, are used everywhere to help organizations make decisions about their design, policies, investment, and operations. They are indispensable.

But if modelling is such a great idea, and such a great help, why do so many things go wrong? Well, there’s good modelling and less good modelling. And it’s hard for the consumers of models — in companies, the Civil Service, government agencies — to know when they’re getting the good stuff. Worse, there’s a lot of comment and advice out there which at best doesn’t help, and perhaps makes things worse.

In 1959, the celebrated scientist and novelist C. P. Snow delivered the Rede Lecture on ‘The Two Cultures’. Snow later published a book developing the ideas as ‘The Two Cultures and the Scientific Revolution’.

A famous passage from Snow’s lecture is the following (it can be found in Wikipedia):

‘A good many times I have been present at gatherings of people who, by the standards of the traditional culture, are thought highly educated and who have with considerable gusto been expressing their incredulity at the illiteracy of scientists. Once or twice I have been provoked and have asked the company how many of them could describe the Second Law of Thermodynamics. The response was cold: it was also negative. Yet I was asking something which is the scientific equivalent of: Have you read a work of Shakespeare’s?

‘I now believe that if I had asked an even simpler question — such as, What do you mean by mass, or acceleration, which is the scientific equivalent of saying, Can you read? — not more than one in ten of the highly educated would have felt that I was speaking the same language. So the great edifice of modern physics goes up, and the majority of the cleverest people in the western world have about as much insight into it as their neolithic ancestors would have had.’

Over the decades since, society has come to depend upon mathematics, and on mathematical models in particular, to a very great extent. Alas, the mathematical sophistication of the great majority of consumers of models has not really improved. Perhaps it has even deteriorated.

So, as mathematicians and modellers, we need to make things work. The starting point for good modelling is communication with the client.

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