We have a new paper on compiler security appearing this morning at EuroS&P.
Up till now, writers of crypto and security software not only have to fight the bad guys. We also have to deal with compiler writers, who every so often dream up some new optimisation routine which spots the padding instructions that we put in to make our crypto algorithms run in constant time, or the tricks that we use to ensure that sensitive data will be zeroised when a function returns. All of a sudden some critical code is optimised away, your code is insecure, and you scramble to figure out how to outwit the compiler once more.
So while you’re fighting the enemy in front, the compiler writer is a subversive fifth column in your rear.
It’s time that our toolsmiths were our allies rather than our enemies. We have therefore worked out what’s needed for a software writer to tell a compiler that a loop really must be executed in constant time, or that a variable really must be set to zero when a function returns. Languages like C have no way of expressing programmer intent, so we do this by means of code annotations.
Doing it properly turns out to be surprisingly tricky, but we now have a working proof of concept in the form of plugins for LLVM. For more details, and links to the code, see the web page of Laurent Simon, the lead author; the talk slides are here. This is the first technical contribution in our research programme on sustainable security.
I’m at the world’s first conference on ethics in mathematics and will be speaking in half an hour. Here are my slides. I will be describing the course I teach to second-year computer scientists on Economics, Law and Ethics. Courses on ethics are mandatory for computer scientists while economics is mandatory for engineers; my innovation has been to combine them. My experience is that teaching them together adds real value. We can explain coherently why society needs rules via discussions of game theory, and then of network effects, asymmetric information and other market failures typical of the IT industry; we can then discuss the limitations of law and regulation; and this sets the stage for both principled and practical discussions of ethics.
Mark Zuckerberg tried to blame Cambridge University in his recent testimony before the US Senate, saying “We do need to understand whether there was something bad going on in Cambridge University overall, that will require a stronger action from us.”
The New Scientist invited me to write a rebuttal piece, and here it is.
Dr Kogan tried to get approval to use the data his company had collected from Facebook users in academic research. The psychology ethics committee refused permission, and when he appealed to the University Ethics Committee (declaration: I’m a member) this refusal was upheld. Although he’d got consent from the people who ran his app, the same could not be said of their Facebook “friends” from whom most of the data were collected.
The deceptive behaviour here has been by Facebook, which creates the illusion of privacy in order to get its users to share more data. There has been a lot of work on the economics and psychology of privacy over the past decade and we now understand the dynamics of advertising markets better than we used to.
One big question is the “privacy paradox”. Why do people say they care about privacy, yet behave otherwise? Part of the answer is about context; and part of it is about learning. Over time, more and more people are starting to pay attention to online privacy settings, despite attempts by Facebook and other online advertising firms to keep changing privacy settings to confuse people.
With luck, the Facebook scandal will be a “flashbulb moment” that will drive lots more people to start caring about their privacy online. It will certainly provide interesting new data to privacy researchers.
I can offer a 3.5-year PhD studentship on radio-frequency side-channel security, starting in October 2018, to applicants interested in hardware security, radio communication, and digital signal processing. Due to the funding source, this studentship is restricted to UK nationals, or applicants who have been resident in the UK for the past 10 years. Contact me for details of the project proposal.
A new Computerphile video explains how we’ve worked out a much better way to track stolen bitcoin. Previous attempts to do this had got entangled in the problem of dealing with transactions that split bitcoin into change, or that consolidate smaller sums into larger ones, and with mining fees. The answer comes from an unexpected direction: a legal precedent in 1816. We discussed the technical details last week at the Security Protools Workshop; a preprint of our paper is here.
Previous attempts to track tainted coins had used either the “poison” or the “haircut” method. Suppose I open a new address and pay into it three stolen bitcoin followed by seven freshly-mined ones. Then under poison, the output is ten stolen bitcoin, while under haircut it’s ten bitcoin that are marked 30% stolen. After thousands of blocks, poison tainting will blacklist millions of addresses, while with haircut the taint gets diffused, so neither is very effective at tracking stolen property. Bitcoin due-diligence services supplant haircut taint tracking with AI/ML, but the results are still not satisfactory.
We discovered that, back in 1816, the High Court had to tackle this problem in Clayton’s case, which involved the assets and liabilities of a bank that had gone bust. The court ruled that money must be tracked through accounts on the basis of first-in, first out (FIFO); the first penny into an account goes to satisfy the first withdrawal, and so on.
Ilia Shumailov has written software that applies FIFO tainting to the blockchain and the results are impressive, with a massive improvement in precision. What’s more, FIFO taint tracking is lossless, unlike haircut; so in addition to tracking a stolen coin forward to find where it’s gone, you can start with any UTXO and trace it backwards to see its entire ancestry. It’s not just good law; it’s good computer science too.
We plan to make this software public, so that everybody can use it and everybody can see where the bad bitcoins are going.
I’m giving a further talk on Tuesday at a financial-risk conference in Paris.
This is the title of a paper that appeared today in PLOS One. It describes a tool we developed initially to assess the gullibility of cybercrime victims, and which we now present as a general-purpose psychometric of individual susceptibility to persuasion. An early version was described three years ago here and here. Since then we have developed it significantly and used it in experiments on cybercrime victims, Facebook users and IT security officers.
We investigated the effects on persuasion of a subject’s need for cognition, need for consistency, sensation seeking, self-control, consideration of future consequences, need for uniqueness, risk preferences and social influence. The strongest factor was consideration of future consequences, or “premeditation” for short.
We offer a full psychometric test in STP-II with 54 items spanning 10 subscales, and a shorter STP-II-B with 30 items to measure first-order factors, but that omits second-order constructs for brevity. The scale is here with the B items marked, and here is a live instance of the survey for you to play with. Once you complete it, there’s an on-the-fly interpretation at the end. You don’t have to give your name and we don’t record your IP address.
We invite everyone to use our STP-II scale – not just in security contexts, but also in consumer and marketing psychology and anywhere else it might possibly be helpful. Do let us know what you find!
Making security sustainable is a piece I wrote for Communications of the ACM and has just appeared in the Privacy and security column of their March issue. Now that software is appearing in durable goods, such as cars and medical devices, that can kill us, software engineering will have to come of age.
The notion that software engineers are not responsible for things that go wrong will be laid to rest for good, and we will have to work out how to develop and maintain code that will go on working dependably for decades in environments that change and evolve. And as security becomes ever more about safety rather than just privacy, we will have sharper policy debates about surveillance, competition, and consumer protection.
Perhaps the biggest challenge will be durability. At present we have a hard time patching a phone that’s three years old. Yet the average age of a UK car at scrappage is about 14 years, and rising all the time; cars used to last 100,000 miles in the 1980s but now keep going for nearer 200,000. As the embedded carbon cost of a car is about equal to that of the fuel it will burn over its lifetime, we just can’t afford to scrap cars after five years, as do we laptops.
For durable safety-critical goods that incorporate software, the long-term software maintenance cost may become the limiting factor. Two things follow. First, software sustainability will be a big research challenge for computer scientists. Second, it will also be a major business opportunity for firms who can cut the cost.
This paper follows on from our earlier work for the European Commission on what happens to safety regulation in the future Internet of Things.
I’m at Financial Crypto 2018 and will try to liveblog some of the sessions in followups to this post.
There have been reports that UDP reflection DDoS attacks based on LDAP (aka CLDAP) have been increasing in recent months. Our network of UDP honeypots (described previously) confirms that this is the case. We estimate there are around 6000 attacks per day using this method. Our estimated number of attacks has risen fairly linearly from almost none at the beginning of 2017 to 5000-7000 per day at the beginning of 2018.
Over the period where Netlab observed 304,146 attacks (365 days up to 2017-11-01) we observed 596,534 attacks. This may be due to detecting smaller attacks or overcounting due to attacks on IP prefixes.
The data behind this analysis is part of the Cambridge Cybercrime Centre’s catalogue of data available to academic researchers.
What Goes Around Comes Around is a chapter I wrote for a book by EPIC. What are America’s long-term national policy interests (and ours for that matter) in surveillance and privacy? The election of a president with a very short-term view makes this ever more important.
While Britain was top dog in the 19th century, we gave the world both technology (steamships, railways, telegraphs) and values (the abolition of slavery and child labour, not to mention universal education). America has given us the motor car, the Internet, and a rules-based international trading system – and may have perhaps one generation left in which to make a difference.
Lessig taught us that code is law. Similarly, architecture is policy. The architecture of the Internet, and the moral norms embedded in it, will be a huge part of America’s legacy, and the network effects that dominate the information industries could give that architecture great longevity.
So if America re-engineers the Internet so that US firms can microtarget foreign customers cheaply, so that US telcos can extract rents from foreign firms via service quality, and so that the NSA can more easily spy on people in places like Pakistan and Yemen, then in 50 years’ time the Chinese will use it to manipulate, tax and snoop on Americans. In 100 years’ time it might be India in pole position, and in 200 years the United States of Africa.
My book chapter explores this topic. What do the architecture of the Internet, and the network effects of the information industries, mean for politics in the longer term, and for human rights? Although the chapter appeared in 2015, I forgot to put it online at the time. So here it is now.