I’m writing a third edition of my best-selling book Security Engineering. The chapters will be available online for review and feedback as I write them.
Today I put online a chapter on Who is the Opponent, which draws together what we learned from Snowden and others about the capabilities of state actors, together with what we’ve learned about cybercrime actors as a result of running the Cambridge Cybercrime Centre. Isn’t it odd that almost six years after Snowden, nobody’s tried to pull together what we learned into a coherent summary?
There’s also a chapter on Surveillance or Privacy which looks at policy. What’s the privacy landscape now, and what might we expect from the tussles over data retention, government backdoors and censorship more generally?
There’s also a preface to the third edition.
As the chapters come out for review, they will appear on my book page, so you can give me comment and feedback as I write them. This collaborative authorship approach is inspired by the late David MacKay. I’d suggest you bookmark my book page and come back every couple of weeks for the latest instalment!
We have yet another “post-doc” position in the Cambridge Cybercrime Centre: https://www.cambridgecybercrime.uk (for the happy reason that Daniel is off to become a Chancellor’s Fellow at Strathclyde).
We are looking for an enthusiastic researcher to join us to work on our datasets of cybercrime activity, collecting new types of data, maintaining existing datasets and doing innovative research using our data. The person we appoint will define their own goals and objectives and pursue them independently, or as part of a team.
An ideal candidate would identify cybercrime datasets that can be collected, build the collection systems and then do cutting edge research on this data — whilst encouraging other academics to take our data and make their own contributions to the field.
We are not necessarily looking for existing experience in researching cybercrime, although this would be a bonus. However, we are looking for strong programming skills — and experience with scripting languages and databases would be much preferred. Good knowledge of English and communication skills are important.
Please follow this link to the advert to read the formal advertisement for the details about exactly who and what we’re looking for and how to apply — and please pay attention to our request that in the covering letter you create as part of the application you should explain which particular aspects of cybercrime research are of particular interest to you.
Security systems are often designed by geeks who assume that the users will also be geeks, and the same goes for the advice that users are given when things start to go wrong. For example, banks reacted to the growth of phishing in 2006 by advising their customers to parse URLs. That’s fine for geeks but most people don’t do that, and in particular most women don’t do that. So in the second edition of my Security Engineering book, I asked (in chapter 2, section 2.3.4, pp 27-28): “Is it unlawful sex discrimination for a bank to expect its customers to detect phishing attacks by parsing URLs?”
Tyler Moore and I then ran the experiment, and Tyler presented the results at the first Workshop on Security and Human Behaviour that June. We recruited 132 volunteers between the ages of 18 and 30 (77 female, 55 male) and tested them to see whether they could spot phishing websites, as well as for systematising quotient (SQ) and empathising quotient (EQ). These measures were developed by Simon Baron-Cohen in his work on Asperger’s; most men have SQ > EQ while for most women EQ > SQ. The ability to parse URLs is correlated with SQ-EQ and independently with gender. A significant minority of women did badly at URL parsing. We didn’t get round to publishing the full paper at the time, but we’ve mentioned the results in various talks and lectures.
We have now uploaded the original paper, How brain type influences online safety. Given the growing interest in gender HCI, we hope that our study might spur people to do research in the gender aspects of security as well. It certainly seems like an open goal!
I’m in the Security Protocols Workshop, whose theme this year is “security protocols for humans”. I’ll try to liveblog the talks in followups to this post.
I’m in the FutureID3 workshop in Jesus College, Cambridge, and will try to liveblog the talks in followups to this post.
I’m at Financial Crypto 2019 and will try to liveblog some of the sessions in followups to this post.
In previous work we have shown how stolen bitcoins can be traced if we simply apply existing law. If bitcoins are “mixed”, that is to say if multiple actors pool together their coins in one transaction to obfuscate which coins belong to whom, then the precedent in Clayton’s Case says that FIFO ordering must be used to track which fragments of coin are tainted. If the first input satoshi (atomic unit of Bitcoin) was stolen then the first output satoshi should be marked stolen, and so on.
This led us to design Taintchain, a system for tracing stolen coins through the Bitcoin network. However, we quickly discovered a problem: while it was now possible to trace coins, it was harder to spot patterns. A decent way of visualizing the data is important to make sense of the patterns of splits and joins that are used to obfuscate bitcoin transactions. We therefore designed a visualization tool that interactively expands the taint graph based on user input. We first came up with a way to represent transactions and their associated taints in a temporal graph. After realizing the sheer number of hops that some satoshis go through and the high outdegree of some transactions, we came up with a way to do graph generation on-the-fly while assuming some restrictions on maximum hop length and outdegree.
Using this tool, we were able to spot many of the common tricks used by bitcoin launderers. A summary of our findings can be found in the short paper here.
As recently posted, we currently advertising a post (details here) where “we expect that the best candidate will be someone from a sociology or criminology background who already has some experience analysing large datasets relating to cybercrime” — and now we have a second post for someone with a more technical background.
We seek an enthusiastic researcher to join us in collecting new types of cybercrime data, maintaining existing datasets and doing innovative research using our data. The person we appoint will define their own goals and objectives and pursue them independently, or as part of a team.
An ideal candidate would identify cybercrime datasets that can be collected, build the collection systems and then do cutting edge research on this data – whilst encouraging other academics to take our data and make their own contributions to the field.
We are not necessarily looking for existing experience in researching cybercrime, although this would be a bonus as would a solid technical background in networking and/or malware analysis. We do seek a candidate with strong programming skills — and experience with scripting languages and databases would be much preferred. Good knowledge of English and communication skills are important.
Details of this second post, and what we’re looking for are in the job advert here: http://www.jobs.cam.ac.uk/job/19543/.
We have a further “post-doc” position in the Cambridge Cybercrime Centre: https://www.cambridgecybercrime.uk.
We are looking for an enthusiastic researcher to join us to work on our datasets of posts made in “underground forums”. In addition to pursuing their own research interests regarding cybercrime, they will help us achieve a better understanding of the research opportunities that these datasets open up. In particular, we want to focus on establishing what types of tools and techniques will assist researchers (particularly those without a computer science background) to extract value from these enormous sets (10’s of millions of posts) of data. We will also be looking to extend our collection and need help to understand the most useful way to proceed.
We have an open mind as to who we might appoint, but expect that the best candidate will be someone from a sociology or criminology background who already has some experience analysing large datasets relating to cybercrime. The appointee should be looking to develop their own research, but also be prepared to influence how cybercrime research by non-technical researchers can be enabled by effective use of the extremely large datasets that we are making available.
Details of the posts, and what we’re looking for are in the job advert here: http://www.jobs.cam.ac.uk/job/19318/.
I am at the Symposium on Post-Bitcoin Cryptocurrencies in Vienna and will try to liveblog the talks in follow-ups to this post.
The introduction was by Bernhard Haslhofer of AIT, who maintains the graphsense.info toolkit and runs the Titanium project on bitcoin forensics jointly with Rainer Boehme of Innsbruck. Rainer then presented an economic analysis arguing that criminal transactions were pretty well the only logical app for bitcoin as it’s permissionless and trustless; if you have access to the courts then there are better ways of doing things. However in the post-bitcoin world of ICOs and smart contracts, it’s not just the anti-money-laundering agencies who need to understand cryptocurrency but the securities regulators and the tax collectors. Yet there is a real policy tension. Governments hype blockchains; Austria uses them to auction sovereign bonds. Yet the only way in for the citizen is through the swamp. How can the swamp be drained?