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?
Over the last thirty years or so, we’ve seen security protocols evolving in different ways, at different speeds, and at different levels in the stack. Today’s TLS is much more complex than the early SSL of the mid-1990s; the EMV card-payment protocols we now use at ATMs are much more complex than the ISO 8583 protocols used in the eighties when ATM networking was being developed; and there are similar stories for GSM/3g/4g, SSH and much else.
How do we make sense of all this?
Reconciling Multiple Objectives – Politics or Markets? was particularly inspired by Jan Groenewegen’s model of innovation according to which the rate of change depends on the granularity of change. Can a new protocol be adopted by individuals, or does it need companies to adopt it en masse for internal use, or does it need to spread through a whole ecosystem, or – the hardest case of all – does it require a change in culture, norms or values?
Security engineers tend to neglect such “soft” aspects of engineering, and we probably shouldn’t. So we sketch a model of the innovation stack for security and draw a few lessons.
Perhaps the most overlooked need in security engineering, particularly in the early stages of a system’s evolution, is recourse. Just as early ATM and point-of-sale system operators often turned away fraud victims claiming “Our systems are secure so it must have been your fault”, so nowadays people who suffer abuse on social media can find that there’s nowhere to turn. A prudent engineer should anticipate disputes, and give some thought in advance to how they should be resolved.
Reconciling Multiple Objectives appeared at Security Protocols 2017. I forgot to put the accepted version online and in the repository after the proceedings were published in late 2017. Sorry about that. Fortunately the REF rule that papers must be made open access within three months doesn’t apply to conference proceedings that are a book series; it may be of value to others to know this!
Google has a number of restrictions on what can be advertised on their advert serving platforms. They don’t allow adverts for services that “cause damage, harm, or injury” and they don’t allow adverts for services that “are designed to enable dishonest behavior“.
Google don’t seem to have an explicit policy that says you cannot advertise a criminal enterprise : perhaps they think that is too obvious to state.
Nevertheless, the policies they written down might lead you to believe that advertising “booter” (or as they sometimes style themselves to appear more legitimate) “stresser” services would not be allowed. These are websites that allow anyone with a spare $5.00 or so to purchase distributed denial of service (DDoS) attacks.
Booters are mainly used by online game players to cheat — by knocking some of their opponents offline — or by pupils who down the school website to postpone an online test or just because they feel like it. You can purchase attacks for any reason (and attack any Internet system) that you want.
These booter sites are quite clearly illegal — there have been recent arrests in Israel and the Netherlands and in the UK Adam Mudd got two years (reduced to 21 months on appeal) for running a booter service. In the USA a New Mexico man recently got a fifteen year sentence for merely purchasing attacks from these sites (and for firearms charges as well).
However, Google doesn’t seem to mind booter websites advertising their wares on their platform. This advert was served up a couple of weeks back:
I complained using Google’s web form — after all, they serve up lots of adverts and their robots may not spot all the wickedness. That’s why they have reporting channels to allow them to correct mistakes. Nothing happened until I reached out to a Google employee (who spends a chunk of his time defending Google from DDoS attacks) and then finally the advert disappeared.
Last week another booter advert appeared:
but another complaint also made no difference and this time my contact failed to have any impact either, and so at the time of writing the advert is still there.
It seems to me that, for Google, income is currently more important than enforcing policies.
Next week we will present a new paper at USENIX WOOT 2018, in which we show that we can find low- and medium-interaction honeypots on the Internet with a few packets. So if you are running such a honeypot (Cowrie, Glastopf, Conpot etc.), then “we know where you live” and the bad guys might soon as well.
In total, we identify 7,605 honeypot instances across nine different honeypot implementations for the most important network protocols SSH, Telnet, and HTTP.
These honeypots rely on standard libraries to implement large parts of the transport layer, but they were never intended to provide identical behaviour to the systems being impersonated. We show that fixing the identity string pretending to be OpenSSH or Apache and not “any” library or fixing other common identifiers such as error messages is not enough. The problem is that there are literally thousands of distinguishing protocol interactions, part of the contribution of the paper is to show how to pick the “best” one. Even worse, to fingerprint these honeypots, we do not need to send any credentials so it will be hard to tell from the logging that you have been detected.
We also find that many honeypots are deployed and forgotten about because part of the fingerprinting has been to determine how many people are not actively patching their systems! We find that 27% of the SSH honeypots have not been updated within the last 31 months and only 39% incorporate improvements from 7 months ago. It turns out that security professionals are as bad as anyone.
We argue that our method is a ‘class break’ in that trivial patches cannot address the issue. Thus we need to move on from the current dominant honeypot architecture of python libraries and python programs for low- and medium-interaction honeypots. We also have developed a modified version of the OpenSSH daemon (sshd) which can front-end a Cowrie instance so that the protocol layer distinguishers will no longer work.
The paper is available here.
I’m at the Cambridge Cybercrime Centre’s Third Annual Cybercrime Conference. I will try to liveblog the event in followups to this post.
I was at The Fifth International Workshop on Graphical Models for Security (part of FLoC 2018) this weekend where I presented a paper. Following is a summarized account of the talks that took place there. Slides can be found here.
The first speaker was Mike Fisk who was giving an invited talk on Intrusion Tolerance in Complex Cyber Systems. Mike started off by elaborating the differences in the construction of physically secure systems such as forts versus the way software engineers go about creating so-called secure systems. He then made the case for thinking in terms of intrusion tolerance rather than just intrusion resistance – even if an intruder gets in, your system should be designed in such a way that it impedes the intruder’s exploration of your network. He then instantiated this idea by talking about credentials for accessing network resource and how they’re stored. He noted that normal users (with the notable exceptions of sysadmins) show predictable access patterns whereas attackers show wildly different access patterns; an intrusion tolerant system should take these into account and ask for re-authentication in case of abnormal patterns. He then talked about metrics for figuring out which nodes in a network are most interesting to an attacker. While some of these are expected – say, the ActiveDirectory server – others are quite surprising such as regular desktops with very high network centrality. He concluded by giving advise on how to use these metrics to direct resources for intrusion resistance most effectively.
Sabarathinam Chockalingam gave a talk on using Bayesian networks and fishbone diagrams to distinguish between intentional attacks and accidental technical failures in cyber-physical systems. His work focused specifically on water level sensors used in floodgates. He first gave an introduction to fishbone diagrams highlighting their salient features such as the ability to facilitate brainstorming sessions while showcasing all the relevant factors in a problem. He then presented a way to translate fishbone diagrams into Bayesian networks. He utilized this technique to convert the risk factor fishbone diagram for the water level sensors into a Bayesian network and generated some predictions. These predictions were mostly based on expert knowledge and literature review. He concluded by pointing at some possible future research directions primary of which was exploring the conversion of fishbone diagrams into conditional probability tables.
I gave a talk on visualizing the diffusion of stolen bitcoins. This works builds upon our previous work on applying the FIFO algorithm to tainting bitcoins, presented at SPW2018. Here, I focused on the challenges facing effective visualization of the tainting dataset. I highlighted the size of the dataset (>450 GB for just 56 kinds of taint), the unbounded number of inputs and outputs as well as the unbounded number of hops a satoshi can take. All these make visualization without abstraction challenging. We refused to use lossy abstractions since what is interesting to the user might be something that we abstract away. Instead, we made two prototypes that, for the most part, convey the underlying information in an accessible manner to the end-user without using any abstractions. The first provides a static map of the taint-graph, useful for getting a global view of the graph; the second provides an interactive way to explore individual transactions. I concluded by pointing out that this is a much more general problem since what we are trying to do is visualize a large subset of transactions in a massive dataset – something that is encountered in many other domains.
Ross Horne presented a specialization of attack trees where he took into consideration of an attacker about the underlying system that they are trying to compromise. He pointed out that existing attack trees assume perfect knowledge on the part of the attacker whereas this is not realistic. The attacker often acts under uncertainty. To model this, he introduced a new operator to act between branches of an attack tree that conveys ignorance on the effectiveness and possible outcomes in case the attacker chooses to traverse that sub-tree. He then introduced a way of reasoning about the specialization of such trees and showed how the placement of the newly introduced operator has varying impact on the capabilities of the attacker. He concluded by remarking how these new attack trees could be used for moving target defence.
Harley Eades III gave a talk on applying linear logic to attack trees. He started off by pointing out that when understanding the difficulty of execution of an attack, we only care about the weights assigned to the leaves of the tree, the root nodes only serve as combinatorial operators. He then presented an exhaustive list of operators and provided a representation to convert attack trees into linear logic statements. He then introduced Maude, a quarternary semantics of attack trees followed by the introduction of Lina, an embedded domain specific programming language. Lina is used to do automated reasoning about attack trees using Maude. He presented Lina’s functionalities and showed an example application of Lina: automated threat analysis. He concluded by talking about future work conjecturing different formal models of causal attack trees specifically mentioning a petri net model.
The Cambridge Cybercrime Centre is organising another one day conference on cybercrime on Thursday, 12th July 2018.
We have a stellar group of invited speakers who are at the forefront of their fields:
- Dave Jevans, CipherTrace
- Gareth Tyson, Queen Mary University of London
- Marleen Weulen Kranenbarg, Vrije Universitaet Amsterdam
- Daniel R. Thomas, Cambridge Cybercrime Centre, University of Cambridge
- Giacomo Persi Paoli, RAND Europe
- David S. Wall, Centre for Criminal Justice Studies, University of Leeds
- J.J. Cardoso de Santanna, University of Twente
- Maria Bada, Global Cyber Security Capacity Centre, University of Oxford
- Sergio Pastrana, Cambridge Cybercrime Centre, University of Cambridge
- Andrew Caines, Faculty of Modern and Medieval Languages, University of Cambridge
- Richard Clayton, Cambridge Cybercrime Centre, University of Cambridge
They will present various aspects of cybercrime from the point of view of criminology, policy, security economics, law and industry.
This one day event, to be held in the Faculty of Law, University of Cambridge will follow immediately after (and will be in the same venue as) the “11th International Conference on Evidence Based Policing” organised by the Institute of Criminology which runs on the 10th and 11th July 2018.
Full details (and information about booking) is here.
I’m at the seventeenth workshop on the economics of information security, hosted by the University of Innsbruck. I’ll be liveblogging the sessions in followups to this post.
We have three open positions in the Cambridge Cybercrime Centre: https://www.cambridgecybercrime.uk.
We wish to fill at least one of the three posts with someone from a computer science, data science, or similar technical background.
BUT we’re not just looking for computer science people: to continue our multi-disciplinary approach, we wish to fill at least one of the three posts with someone from a criminology, sociology, psychology or legal background.
Details of the posts, and what we’re looking for are in the job advert here: http://www.jobs.cam.ac.uk/job/17827/.
Bitcoin Redux explains what’s going wrong in the world of cryptocurrencies. The bitcoin exchanges are developing into a shadow banking system, which do not give their customers actual bitcoin but rather display a “balance” and allow them to transact with others. However if Alice sends Bob a bitcoin, and they’re both customers of the same exchange, it just adjusts their balances rather than doing anything on the blockchain. This is an e-money service, according to European law, but is the law enforced? Not where it matters. We’ve been looking at the details.
In March we wrote about how to trace stolen bitcoin, describing new tools that enable us to track crime proceeds on the blockchain with more precision than before. We waited for victims of bitcoin theft and fraud to come to us, so we could test our tools on real cases. However in most of them it was not clear that the victims had ever owned any bitcoin at all.
There are basically three ways you could try to hold a bitcoin. You could buy one from an exchange and get them to send it to a wallet you host yourself, but almost nobody does that.
You could buy one from an exchange and get the exchange to keep the keys for you, so that the asset was unique to you and they were only guarding it for you – just like when you buy gold and the bullion merchant then charges you a fee to guard your gold in his vault. If the merchant goes bust, you can turn up at the vault with your receipt and demand your gold back.
Or you could buy one from an exchange and have them owe you a bitcoin – just as when you put your money in the bank. The bank doesn’t have a stack of banknotes in the vault with your name on it; and if it goes bust you have to stand in line with the other creditors.
It seems that most people who buy bitcoin think that they’re operating under the gold merchant model, while most exchanges operate under the bank model. This raises a whole host of issues around solvency, liquidity, accounting practices, money laundering, risk and trust. The details matter, and the more we look at them, the worse it seems.
This paper will appear at the Workshop on the Economics of Information Security later this month. It contains eight recommendations for what governments should be doing to clean up this mess.