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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Gianluca Stringhini – Cyber criminal operations and developing systems to defend against them

Gianluca Stringhini’s research focuses on studying cyber criminal operations and developing systems to defend against them.

Such operations tend to follow a common pattern. First the criminal operator lures a user into going to a Web site and tries to infect them with malware. Once infected, the user is joined to a botnet. From there, the user’s computer is instructed to perform malicious activities on the criminal’s behalf. Stringhini, whose UCL appointment is shared between the Department of Computer Science and the Department of Security and Crime Science, has studied all three of these stages.

Stringhini, who is from Genoa, developed his interest in computer security at college: “I was doing the things that all college students are doing, hacking, and breaking into systems. I was always interested in understanding how computers work and how one could break them. I started playing in hacking competitions.”

At the beginning, these competitions were just for fun, but those efforts became more serious when he arrived in 2008 at UC Santa Barbara, which featured one of the world’s best hacking teams, a perennial top finisher in Defcon’s Capture the Flag competition. It was at Santa Barbara that his interest in cyber crime developed, particularly in botnets and the complexity and skill of the operations that created them. He picked the US after Christopher Kruegel, whom he knew by email, invited him to Santa Barbara for an internship. He liked it, so he stayed and did a PhD studying the way criminals use online services such as social networks

“Basically, the idea is that if you have an account that’s used by a cyber criminal it will be used differently than one used by a real person because they will have a different goal,” he says. “And so you can develop systems that learn about these differences and detect accounts that are misused.” Even if the attacker tries to make their behaviour closely resemble the user’s own, ultimately spreading malicious content isn’t something normal users intend to do, and the difference is detectable.

This idea and Stringhini’s resulting PhD research led to his most significant papers to date.

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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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What are the social costs of contactless fraud?

Contactless payments are in the news again: in the UK the spending limit has been increased from £20 to £30 per transaction, and in Australia the Victoria Police has argued that contactless payments are to blame for an extra 100 cases of credit card fraud per week. These frauds are where multiple transactions are put through, keeping each under the AUS $100 (about £45) limit. UK news coverage has instead focussed on the potential for cross-channel fraud: where card details are skimmed from contactless cards then used for fraudulent online purchases. In a demonstration, Which? skimmed volunteers cards at a distance then bought a £3,000 TV with the card numbers and expiry dates recorded.

The media have been presenting contactless payments are insecure; the response from the banking industry is to point out that customers are not liable for the fraudulent transactions. Both are in some ways correct, but in other ways are missing the point.

The law in the UK (Payment Services Regulations (PSR) 2009, Regulation 62) indeed does say that the customers are entitled to a refund for fraudulent transactions. However a bank will only do this if they are convinced the customer has not authorised the transaction, and was not negligent. In my experience, a customer who is unable to clearly, concisely and confidently explain why they are entitled to a refund runs a high risk of not getting one. This fact will disproportionately disadvantage the more vulnerable members of society.

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Experimenting with SSL Vulnerabilities in Android Apps

As the number of always-on, always-connected smartphones increase, so does the amount of personal and sensitive information they collect and transmit. Thus, it is crucial to secure traffic exchanged by these devices, especially considering that mobile users might connect to open Wi-Fi networks or even fake cell towers. The go-to protocol to secure network connection is HTTPS i.e., HTTP over SSL/TLS.

In the Android ecosystem, applications (apps for short), support HTTPS on sockets by relying on the android.net, android.webkit, java.net, javax.net, java.security, javax.security.cert, and org.apache.http packages of the Android SDK. These packages are used to create HTTP/HTTPS connections, administer and verify certificates and keys, and instantiate TrustManager and HostnameVerifier interfaces, which are in turn used in the SSL certificate validation logic.

A TrustManager manages the certificates of all Certificate Authorities (CAs) used to assess a certificate’s validity. Only root CAs trusted by Android are contained in the default TrustManager. A HostnameVerifier performs hostname verification whenever a URL’s hostname does not match the hostname in the peer’s identification credentials.

While browsers provide users with visual feedback that their communication is secured (via the lock symbol) as well as certificate validation issues, non-browser apps do so less extensively and effectively. This shortcoming motivates the need to scrutinize the security of network connections used by apps to transmit user sensitive data. We found that some of the most popular Android apps insufficiently secure these connections, putting users’ passwords, credit card details and chat messages at risk.

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Teaching Privacy Enhancing Technologies at UCL

Last term I had the opportunity and pleasure to prepare and teach the first course on Privacy Enhancing Technologies (PETs) at University College London, as part of the MSc in Information Security.

The course covers principally, and in some detail, engineering aspects of PETs and caters for an audience of CS / engineering students that already understands the basics of information security and cryptography (although these are not hard prerequisites). Students were also provided with a working understanding of legal and compliance aspects of data protection regimes, by guest lecturer Prof. Eleni Kosta (Tilburg); as well as a world class introduction to human aspects of computing and privacy, by Prof. Angela Sasse (UCL). This security & cryptographic engineering focus sets this course apart from related courses.

The taught part of the course runs for 20 hours over 10 weeks, split in 10 topics:

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UCL Code Breaking Competition

6689260_sModern security systems frequently rely on complex cryptography to fulfil their goals and so it is important for security practitioners to have a good understanding of how cryptographic systems work and how they can fail. The Cryptanalysis (COMPGA18/COMPM068) module in UCL’s MSc Information Security provides students with the foundational knowledge to analyse cryptographic systems whether as part of system development in industry or as academic research.

To give students a more realistic (and enjoyable) experience there is no written exam for this module; instead the students are evaluated based on coursework and a code breaking competition.

UCL has a strong tradition of experimental research and we have been running many student competitions and hacking events in the past. In March 2013 a team directed by Dr Courtois won the UK University Cipher Challenge 2013 award, held as part of the UK Cyber Security Challenge.

This year the competition has been about finding cryptographically significant events in a real-life financial system. The competition (open both to UCL students and those of other London universities) requires the study of random number generators, elliptic curve cryptography, hash functions, exploration of large datasets, programming and experimentation, data visualisation, graphs and statistics.

We are pleased to announce the winners of the competition:

  • Joint 1st prize: Gemma Bartlett. Grade obtained 92/100.
  • Joint 1st prize: Vasileios Mavroudis.  Grade obtained 92/100.
  • 2nd prize: David Kohan Marzagão.  Grade obtained 82/100.

About the winners:

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  • Gemma Bartlett (left) is in her final year at UCL studying for an M.Eng. in Mathematical Computation with a focus on Information Security. Her particular interests include digital forensics. She will be starting a job in this field after graduation.
  • Vasilios Mavroudis (middle) received his B.Sc. in Applied Informatics from the University of Macedonia, Greece in 2012.  He is currently pursuing an M.Sc. in Information Security at UCL. In the past, he has worked as a security researcher in Deutsche Bank, University of California Santa Barbara and at the Centre for Research and Technology Hellas (CERTH). His research interests include network and systems security, malware, and applied cryptography.
  • David Kohan Marzagão (right) is currently undertaking a PhD in Computer Science under the supervision of Peter McBurney at King’s College London.  In 2014, he received his BSc in Mathematics at the University of São Paulo, Brazil. His research interests include cryptography, multi-agent systems, graph theory, and random walks.

Measuring Internet Censorship

Norwegian writer Mette Newth once wrote that: “censorship has followed the free expressions of men and women like a shadow throughout history.” Indeed, as we develop innovative and more effective tools to gather and create information, new means to control, erase and censor that information evolve alongside it. But how do we study Internet censorship?

Organisations such as Reporters Without Borders, Freedom House, or the Open Net Initiative periodically report on the extent of censorship worldwide. But as countries that are fond of censorship are not particularly keen to share details, we must resort to probing filtered networks, i.e., generating requests from within them to see what gets blocked and what gets through. We cannot hope to record all the possible censorship-triggering events, so our understanding of what is or isn’t acceptable to the censor will only ever be partial. And of course it’s risky, or even outright illegal, to probe the censor’s limits within countries with strict censorship and surveillance programs.

This is why the leak of 600GB of logs from hardware appliances used to filter internet traffic in and out of Syria was a unique opportunity to examine the workings of a real-world internet censorship apparatus.

Leaked by the hacktivist group Telecomix, the logs cover a period of nine days in 2011, drawn from seven Blue Coat SG-9000 internet proxies. The sale of equipment like this to countries such as Syria is banned by the US and EU. California-based manufacturer Blue Coat Systems denied making the sales but confirmed the authenticity of the logs – and Dubai-based firm Computerlinks FZCO later settled on a US$2.8m fine for unlawful export. In 2013, researchers at the University of Toronto’s Citizen Lab demonstrated how authoritarian regimes in Saudi Arabia, UAE, Qatar, Yemen, Egypt and Kuwait all rely on US-made equipment like those from Blue Coat or McAfee’s SmartFilter software to perform filtering.

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Understanding Online Dating Scams

Our research on online dating scams will be presented at the  Conference on Detection of Intrusions and Malware and Vulnerability Assessment (DIMVA) that will be held in Milan in July. This work was a collaboration with colleagues working for Jiayuan, the largest online dating site in China, and is the first large-scale measurement of online dating scams, comprising a dataset of more than 500k accounts used by scammers on Jiayuan across 2012 and 2013.

As someone who has spent a considerable amount of time researching ways to mitigate malicious activity on online services, online dating scams picked my interest for a number of reasons. First, online dating sites operate following completely different dynamics compared to traditional online social networks. On a regular social network (say Facebook or Linkedin) users connect with people they know in real life, and any request to connect from an unknown person is considered unsolicited and potentially malicious. Many malicious content detection systems (including my own) leverage this observation to detect malicious accounts. Putting people who don’t know each other in contact, however, is the main purpose of online dating sites – for this reason, traditional methods to detect fake and malevolent accounts cannot be applied to this context, and the development of a new threat model is required. As a second differentiator, online dating users tend to use the site only for the first contact, and move to other media (text messages, instant messaging) after that. Although that is fine for regular use, it makes it more difficult to track scammers, because the online dating site loses visibility of the messages exchanged between users after they have left the site. Third, online dating scams have a strong human component, which differentiates them heavily from traditional malicious activity on online services such as spam, phishing, or malware.

We identified three types of scams happening on Jiayuan. The first one involves advertising of  escort services or illicit goods, and is very similar to traditional spam. The other two are far more interesting and specific to the online dating landscape. One type of scammers are what we call swindlers. For this scheme, the scammer starts a long-distance relationship with an emotionally vulnerable victim, and eventually asks her for money, for example to purchase the flight ticket to visit her. Needless to say, after the money has been transferred the scammer disappears. Another interesting type of scams that we identified are what we call dates for profit. In this scheme, attractive young ladies are hired by the owners of fancy restaurants. The scam then consists in having the ladies contact people on the dating site, taking them on a date at the restaurant, having the victim pay for the meal, and never arranging a second date. This scam is particularly interesting, because there are good chances that the victim will never realize that he’s been scammed – in fact, he probably had a good time.

In the paper we analyze the accounts that we detected belonging to the different scam types, and extract typical information about the demographics that scammers pose as in their accounts, as well as the demographics of their victims. For example, we show that swindlers usually pose as widowed mid-aged men and target widowed women. We then analyze the modus operandi of scam accounts, showing that specific types of scam accounts have a higher chance of getting the attention of their victims and receiving replies than regular users. Finally, we show that the activity performed on the site by scammers is mostly manual, and that the use of infected computers and botnet to spread content – which is prominent on other online services – is minimal.

We believe that the observations provided in this paper will shed some light on a so far understudied problem in the field of computer security, and will help researchers in developing systems that can automatically detect such scam accounts and block them before they have a chance to reach their victims.

The full paper is available on my website.

Update (2015-05-15): There is press coverage of this paper in Schneier on Security and BuzzFeed.

Teaching cybersecurity to criminologists

I recently had the pleasure of teaching my first module at UCL, an introduction to cybersecurity for students in the SECReT doctoral training centre.

The module had been taught before, but always from a fairly computer-science-heavy perspective. Given that the students had largely no background in computer science, and that my joint appointment in the Department of Security and Crime Science has given me at least some small insight into what aspects of cybersecurity criminologists might find interesting, I chose to design the lecture material largely from scratch. I tried to balance the technical components of cybersecurity that I felt everyone needed to know (which, perhaps unsurprisingly, included a fair amount of cryptography) with high-level design principles and the overarching question of how we define security. Although I say I designed the curriculum from scratch, I of course ended up borrowing heavily from others, most notably from the lecture and exam material of my former supervisor’s undergraduate cybersecurity module (thanks, Stefan!) and from George’s lecture material for Introduction to Computer Security. If anyone’s curious, the lecture material is available on my website.

As I said, the students in the Crime Science department (and in particular the ones taking this module) had little to no background in computer science.  Instead, they had a diverse set of academic backgrounds: psychology, political science, forensics, etc. One of the students’ proposed dissertation titles was “Using gold nanoparticles on metal oxide semiconducting gas sensors to increase sensitivity when detecting illicit materials, such as explosives,” so it’s an understatement to say that we were approaching cybersecurity from different directions!

With that in mind, one of the first things I did in my first lecture was to take a poll on who was familiar with certain concepts (e.g., SSH, malware, the structure of the Internet), and what people were interested in learning about (e.g., digital forensics, cryptanalysis, anonymity). I don’t know what I was expecting, but the responses really blew me away! The students overwhelmingly wanted to hear about how to secure themselves on the Internet, both in terms of personal security habits (e.g., using browser extensions) and in terms of understanding what and how things might go wrong. Almost the whole class specifically requested Tor, and a few had even used it before.

This theme of being (pleasantly!) surprised continued throughout the term.  When I taught certificates, the students asked not for more details on how they work, but if there was a body responsible for governing certificate authorities and if it was possible to sue them if they misbehave. When I taught authentication, we played a Scattergories-style game to weigh the pros and cons of various authentication mechanisms, and they came up with answers like “a con of backup security questions is that they reveal cultural trends that may then be used to reveal age, ethnicity, gender, etc.”

There’s still a month and a half left until the students take the exam, so it’s too soon to say how effective it was at teaching them cybersecurity, but for me the experience was a clear success and one that I look forward to repeating and refining in the future.