The UK goes every ten years through a national census, where every household is called to fill in details about their demographics, habits, travel and income. The next one will be the UK 2011 census.

The office for national statistics has a statutory duty to ensure that the data released from this census cannot be used to identify any individual or to infer any of unknown attribute. Techniques for doing so are called statistical disclosure control, and have been the subject of intense study for the last 40 years at least. One could never have guessed by reading the documents on confidentiality for the next UK census.

To make a long story short: the ONS never considered modern well defined notions of privacy, it lacks a reliable evaluation framework to establish the degree of risk of different methods (let alone utility), and has proposed disclosure control measures that fall rather short of the state of the art.

Moving households around (a bit)

The consultation is not totally over yet, but the current favorite after two rounds of evaluation seems to be a technique called “Record Swapping”. How does it work? The technique takes the database of all responses to the census and outputs another database, that is sufficiently different to avoid identification and inference. Record swapping first categorises all records by the household size, sex, broad age, and hard-to-count variables. Then it selects 2-20% of the records, and each of them are paired with a record from the same category. Then the geographical data of each pair of records (yes, right, only the geographical data) are swapped.

This procedure has the effect to disperse geographically the population a bit so that, it is not possible to know whether single cells in tables are indeed providing information about an individual in a region or, whether they are the product of a swap from a different region. The advantage is that the totals are the same (since swapping things around is invariant to addition), the swaps are with “similar” households, and the procedure is simple to implement.

This is in-line with the definition of privacy of the census office, namely that: 

“The Registrars General concluded that the Code of Practice statement can be met in relation to census outputs if no statistics are produced that allow the identification of an individual (or information about an individual) with a high degree of confidence. The Registrars General consider that, as long as there has been systematic perturbation of the data, the guarantee in the Code of Practice would be met.”

Problems with “Record Swapping”

So far a whole process has been followed to evaluate a list of proposed disclosure control measures, present a methodolody to evaluate them, shortlist some, and perform more in-depth research about their utility and privacy. There is a lot of repetition in these documents, a few ad-hoc indicators of quality and privacy, and no security analysis what-so-ever about inference attacks on the proposed schemes. The subject of ” disclosure by differencing” is left as a suggestion for future work in the latest interim report, while the only method left on the list is Record Swapping, as well as ABS, that has apparently not been tested yet at all.

Why is that a problem? Records include many other potentially identifying fields aside from location. Since the rest of the record stand as it is, and is aggregated into tables, with a secret small cell adjustment technique, we cannot really be sure at all that there are no re-identification attacks. (Apparently revealing the details of the technique cannot be divulged for confidentiality reasons, violating even the most basic principle of security engineering! See page 3).

The utility measures used to assess how acceptable these disclosure control measures will be to data users (Shlomo et al.), are themselves very simplistic and do not offer very tight bounds on possible errors but I will leave this matter for the statisticians to blog about.

To make the problem worse, this time the ONS, is seriously thinking of allowing data users to submit their own queries to the database of statistics. The queries are not likely to be full SQL any time soon, but tables on 3 categories (called cubes) are likely to be allowed. This leaves wide open quite a range of attacks in the literature on inference in statistical databases.

At this point there is absolutely no evidence that the disclosure control scheme is actually secure, which in security engineering means that it is probably not.

How did we get to this situation?

It seems the bulk of the work on disclosure control has been done by the ONS, in conjunction with researchers from the University of Southampton. None of the authors of any of the evaluations has a substancial research experience in privacy technology or theoretical computer security that deals with these privacy matters in a systematic way.

What is revealing is the fact that the most relevant related work is never mentioned. It includes:

• The work of Denning on trackersand inference in statistical databases (1980). Instead the archaic term “differencing” is used.
• The work of Sweeney and Samarati on linkage attacks and k-anonymity (1997).
• The work of Dwork on Differential Privacy (2007), which is the most current and strongest definition of privacy for statistical databases.

These works show repeatedly that ad-hoc inference control measures, that only aim to suppress a handful of known and obvious attacks, are systematically bypassed.

Dwork in her work on Differential Privacy (that won the 2009 year’s PET Award) provides clear arguments on why simpler ad-hoc techniques cannot provide the same guarantee of privacy: their results can be aggregated with side information known to the adversary to facilitate inference. Differential privacy on the other hand guarantees that the results of a query to the database, or published table, reveals no more information when composed with other such queries or any side information. 

This is a hot topic in research today, and all the details may not be ready for a census in 2 years time. This does not justify the ONS’s ignorance of this field.

Micah Sherr presented at PETS a few days ago his work on ”Scalable Link-Based Relay Selection for Anonymous Routing“. The key idea is that paths are generated by taking into account the network performance of each link to be used. The overhead of distributing performance information can be reduced by associating with each server a network coordinate, that allows to estimate the latency between pairs of nodes.

This is a pure path selection proposal, as quite a few have appeared in the past year to reduce latency, or increase node utilization in Tor. The question with all those proposals is: how much anonymity would these path selection strategies provide?

The methodology we present in  “The Bayesian Traffic Analysis of Mix Networks” provides a way of answering such questions, by carefully modelling the path selection strategy. Applying the same methodology to these path selection proposals would be of clear benefit, and an excellent project for anyone interested in understanding better how to apply inference based techniques to traffic analysis.

Today morning at PETS 2009, the paper on “Physical Layer Attacks on Unlinkability in Wireless LANs” was presented. The idea is that despite all anonymization techniques at the logical layers, though IP address modulation, the physical location of the IEEE802.11 transmitters can be localised, and thus unlinkable packets emanating from it linked together.

The approach used to do this, uses signal strength and triangulation techniques, with a machine learning twist, to cluster together emissions and link them to the same transmitter. A set of countermeasures is also presented, where transmitters modulate their signal strength to foil this clustering.

The attacker model was restricted to using commodity hardware, so physical device fingerprinting attacks were not considered.

In the last year, we have been developping a set of systematic techniques to analyse anonymity systems, to perform traffic analysis. These cast the problem of traffic analysis as a Bayesian inference problem, where the adversay observes some traces, according to a threat model, and then has to infer the hidden state of the system, that is equivalent to tracing who is talking to whom.

So far we have looked at the analysis of mix networks, the analysis of Crowds, and a Bayesian approach to long term intersection attacks. The papers describing each of these are available online:

• Carmela Troncoso and George Danezis.
  The Bayesian Traffic Analysis of Mix Networks. (Draft)
  ACM CCS 2009, Chicago, USA.
• George Danezis, Claudia Diaz, Emilia Kasper, and Carmela Troncoso.
  The wisdom of Crowds: attacks and optimal constructions.
  ESORICS 2009, St Malo, France.
• George Danezis and Carmela Troncoso.
  Vida: How to use Bayesian inference to de-anonymize persistent communications.
  PETS 2009, Seattle, USA.

I just sat thought the first session of PET2009, that was about privacy policies where two really interesting pieces of research were presented.

Ram presented a work on “Capturing Social Networking Privacy Preferences” [pdf], where he proposes to infer automatically privacy policies for social networks, and present them as templates or starting points for users to define their own policies. The methodology used is really neat: they record the location of a number of users, and every night they ask the users whether they would be happy to share their locations with different circles of theirs. Then they try to extract a set of standard policies, based on time, location, and the type of contact that can see your location.

The second study, presented by Aleecia, is on how easy and pleasing is to read privacy policies (“A Comparative Study of Online Privacy Policies and Formats“). They find that privacy policies in different formats are more or less easy to read and understand, but across the board privacy policies are difficult to understand, easy to misunderstand, and totally unpleasant to read.

In the 1950’s Lambros D. Callimahos built the Zendian Problem [zip] as an integrated exercise in traffic analysis, cryptanalysis, and communications intelligence operations. The state of cryptology today has moved on, beyond the point where an analyst can rely on plaintext to drive operations. The state of traffic analysis techniques, and the availability of more computing power, requires a new generation of exercises to sharpen the tools and minds of those in the field.

Steven Murdoch and myself have been developing, on (and mostly) off, over the past year an exercise in traffic analysis, and in particular the long term disclosure attacks. The exercise was first presented and used at the Brno FIDIS summer school, and we are now using it as part of an industrial training curriculum.

The exercise consists of an anonymized trace of communications, that were mediated by an anonymity system, that a group of people used to message each other. The message traces are synthetic,  but generated based on a real-world social network. Users have favorite communication partners, talk more or less according to the type of relationship and time of day, and may reply to each others messages.

The goal is to apply any disclosure attacks, and de-anonymize and trace as many messages as possible. An oracle is provided that outputs the success rate, and the instructor’s pack includes the original messages as well as the scripts used to simulate the messaging behaviours and the anonymization layer. We tried to keep the exercise and success rates realistic, so do not expect to ever get 100% — significantly better than random is already quite good.

The richness of the messaging behaviour is designed to stress the most advanced statistical disclosure techniques, that make use of social network, replies, and perfect matchings. The literature on statistical disclosure can be found on the exercise page, and an example implementing the simple SDA is provided in the bundle. The family of Disclosure Attacks (devised by Kesdoganet al.) might also be modified and applied to the exercise. Our new attack soon to be presented at PET, using Bayesian Inference, could also be applied:

• George Danezis and Carmela Troncoso. Vida: How to use Bayesian inference to de-anonymize persistent communications. Privacy Enhancing Technologies Symposium (PETS 2009), Seattle, USA.

A couple of caveats: this is an exercise, to help people learn about long term traffic analysis attacks, and allow them to implement the attacks on a rich, but safe, dataset. The objective is to learn.

1. It is not a benchmarking tool between attacks. We are not sure that the traffic patterns are typical enough to make sure that when an attack performs better in the setting of our exercise it would perform better on real data.
2. It is also not a competition or test. We publish all of the hidden state for instructors, and the random number generator used was not cryptographically strong. The point is not who can get the highest score, but the quality of understanding of the attacks.

Caveats aside, I do hope that the exercise opens a discussion about how we can exchange training or live datasets, formats for evaluating traffic analysis attacks, and a level of standardisation to the interfaces of attack scripts. These will probably be topics for debate over the Privacy Enhancing Technologies Symposium 2009, next week.

Both myself and Steven would be very interested to hear your experiences with the exercise, either if you take it yourself, or give it to a class as an instructor. If you extend the exercise, or generate particular bundles of anonymized datasets, we would also be happy to host them.

The annual reports from the Chief Surveillance Commissioner (2008-2009) and the Interception of Communications Commissioner (2008)just came out. They contain some interesting statistics, buried in the mist of boring self-congratulations on how wonderful the surveillance regime is in the UK.

First of all we get a bit of an idea on how, and how often, the RIPA part III powers to compel decryption or request keys, are to be used. It seems, from both reports, that any such request has to be approved by NTAC first, before anyone is served. Then a judge rubber-stamps the request that is served to an individual. These individual comply or go to jail, the theory goes. In the period 2008-2009:

• NTAC approved 26 applications to serve a decryption notice (and declined 1).
• A judge approved 17 notices (and zero were declined).
• 15 notices were served.
• 11 individuals failed to comply (the assumption is that 4 of them complied)
• 7 individuals were charged as a result of their failure to comply
• 2 individuals were convicted

What does all this add to? About 10% or less conviction rate for failing to comply with a notice (2 / 22, assuming 4 complied). It would of course be of interest to find out if any of those who complied were charged and convicted with any offences, or whether the requests are just keeping honest people honest.

It is a real pity more qualitative information is not provided about the specific cases that reached court, aside the fact that the powers were used to investigate counter terrorism, child indecency and domestic extremism. Finding how each case went would be quite worth while.

The appendix B of the Surveillance Commissioner has a rough breakdown of the authorisations for property interference as well as surveillance, by types of offence investigated. The trends, and changes, between this period (2008-2009) and the previous period (2007-2008) are very interesting, and again totally unexplained in the text of the report. Some highlights:

• Most of the authorisations for property interference are related to drugs offenses (63% in 2008-2009, and 60% in 2007-2008). That seems pretty stable, and is the single biggest category by an order of magnitude.
• We used to have a terrorism problem, with about 4.8% of property interference related to it in 2007-2008. It seems we have ran out of terrorism to investigate in 2008-2009, and now it only accounts for 0.6% of all cases of property interference. That is nearly an order of magnitude reduction.
• While terrorism is down, conspiracy investigations are up: 2.8% of authorisations related to it in 2008-2009, versus only 1.5% for the previous year. That may not be unrelated to the shift of looking at “domestic terrorism”, with the usual silly “conspiracy to cause a nuisance” charges.
• It is unclear where child indicency fits in any of these categories, despite requiring some property interference, presumably to raid people and seize their computers.

Similar trends are observed when it comes to intrusive surveillance authorised under RIPA Part II. Drugs are biger than anything else, terrorism is no more a pretext for surveillance (1 case!) and conspiracy is becoming popular with a serious increase of surveillance. The investigations of burglaries and robberies using surveillance and property interference is also up. About 2681 property interference authorisations were issued, and 384 intrusive surveilance authorisations were served in 2008-2009. (There were also 16118 directed surveillance authorisations.)

The interception of communication figures look relatively similar. In 2008 about the same number of warrants were issued or active under RIPA (2599 RIPA warrants) for intercepting communications. The fact that the numbers are of the same order of magnitude may suggest that the different authorisations are used as a “bundle” for particular cases. It might also be just a coincidence.

There are no specific figures about access to traffic data (under traffic data retention regimes) but it is estimated that out of all requests 80% concern subscriber information, e.g. who is behind this telephone number? This is in-line with previous statistics.

What about CHIS, the euphemism for Covert Human Intelligence Source, or more commonly known as a “snitch“? There were 3722 CHIS at the end of March 2009, and 4278 recruited in the year. This means that on average each CHIS is used for a bit less than a year. The variance can of course be significant.

Overall the pictured offered is that the UK is a really quiet place. With about 60 Million people and only about 3000-4000 cases requiring surveillance authorisations, let alone the laughable 26 applications to coerce decryption, there seems to be more rhetoric about serious crime, than there is serious crime. Of course there statistics exclude warrants obtained by MI5 and SIS, who are subject to a different oversight body, that is much less keen on publishing statistics. It is not unlikely that a lot of the terrorism and political crimes are investigated there.

I just come back from a visit to COSIC at K.U. Leuven, to teach a course on Computer Security. Claudia Diaz and myself discussed over lunch the idea of putting together a syllabus for Privacy Technologies. Many in this field have been teaching courses and giving guest lectures, but there does not seem to be yet a canonical curriculum, describing that an advanced course in Privacy Technology should teach.

Here is my attempt at proposing such a syllabus — which I will probably revise after discussions at PETS 2009 next week.

1. An introduction to Privacy Technology
   An overview of the basic concepts, different fields like technology and law, motivation, threat models, Soft versus Hard privacy technology.
   Slides from the 2007 COSIC course: Introduction to Privacy Technology [pdf]
   (Claudia Diaz has vastly improved these slides to present a lecture on the same topic in this years COSIC course.)
2. Privacy in authentication
   Modern authentication protocols, initiator privacy and responder privacy, JFKi and JFKr examples, secure password authentication, PAK.
   Slides from Estonia computer security course in 2007: Secure authentication[pdf, start at slide 3]
3. Selective Disclosure Credentials
   Zero knowledge proofs, selective disclosure for discrete logs, Brands credentials, CL signatures and CL credentials, e-cash, abuse prevention.
   Slides from Estonia computer security course in 2007: Anonymous credentials[pdf, start at slide 45]
4. Anonymous communications
   Proxies, Crowds, DC networks, mix networks and onion routing.
   Slides from ITE talk in 2006: Introducing Anonymous Communications[pdf]
5. An introduction to traffic analysis
   History, identification, information extraction, military applications, internet security, traffic data availability
   Slides from SantaCrypt 2005 in Prague: An introduction to traffic analysis[pdf]
6. The traffic analysis of anonymous communications
   Cryptographic attacks, long term intersection and disclosure, short term disclosure, bridging, network discovery.
   Slides from Umass Amherst talk: Introduction to traffic analysis[pdf]
7. Privacy in Databases
   Inference control, k-anonymity, differential privacy, perturbation, trackers.
   Slides from CFP 2007: Privacy in Databases[pdf, start at slide 58]
8. Privacy in Storage
   Encrypted storage, steganographic storage, remote storage, traffic analysis of storage protocols.
9. Secure Elections
   Electronic voting technologies, secure crypto elections, manual zero-knowledge proofs, receipt freeness, robust mixing.
10. Censorship resistance and availability
    Blocking technologies, counter-blocking technologies, RF technologies, peer-to-peer file sharing, decentralisation and reputation technologies, sybil attacks.
11. Location privacy
    Location based services, Mix zones, ad-hoc network privacy, location privacy friendly location services (PriPAYD), charging schemes.
12. Identity management protocols
    Federated identity management, Liberty, InfoCards, OpenID, PRIME project concepts, privacy policies, P3p, SecPAL.
13. Economic, legal and policy issues of Privacy Technology
    Privacy economics & attitudes, data protection, data retention, interception by design, lawful access, coercion, privacy as a right, health information.

Note that the order of the topics is arbitrary, and mostly related to what slides I have already available. One could start with less technical subjects and then go to the more cryptographic and statistical topics. If anyone has any nice pointers to slide decks for the topics that have none for the moment, I would appriciate them.

The ACLU and the BBC have today posted the first memo, dated 1 August 2002, authorising the use of torture by the CIA against Abu Zubaydah, described as “one of the highest ranking members ofAl Qaeda”. Interestingly one of the enablers for passing into an “increased pressure phase” (you have to love these euphemisms) comes down to traffic analysis, as this passage suggests:

According to the document “intelligence indicates that there is currently a level of `chatter’ equal to that which preceded the September 11 attacks”. It is not comforting at all to know that such automatic processing, as well as subjective interpretation, can be used to start torturing people, in the absence of any other concrete evidence.

Update: Steven Murdoch points to the Washington Post article clarifying the role of the Abu Zubaida as being nowhere near as important as initially assumed. The article states that “Abu Zubaida was not even an official member of al-Qaeda”. Worth reading in its entirety.

There is a tendency amongst privacy advocates in the UK to focus on mistakes, or false positives, of ubiquitous surveillance, as well as small scale “disproportionate” uses of surveillance. These two are the key arguments used to fend off plans to increase the level of data collection. 

In the first case the argument is that perfectly honest people might be mistaken for crooks because of the imperfect view that any data collection system provides the authorities. Any automated decisions, the argument goes, will inevitably flag up Innocent people, while miss the sought targets, since they will be using an array of evasion tactics to foil it. In its essence, this first criticism is true, but can easily be countered by a good oversight mechanism, including human judgement in the loop, as well as pointing out that the bad guys will never have perfect discipline in implementing counter surveillance measures, and if they do it will be at a great cost. Needless to say the false positive / false negative argument has not been very successful, even though it is a good one.

The second argument is based on proportionality: once surveillance powers are in place for one purpose, such as the prevention of serious crime or terrorism, they will inevitably be used for other unforeseen and disproportionate aims. The key recent example is how local UK authorities are using directed surveilance powers to prevent littering and dog fouling. Similar fears have been expressed about traffic data retention that could be used as part of civil cases, or simply seized for any crime what so ever using established evidence collection laws. Again, this argument is valid but a good oversignt mechanism can take care of those cases, at least in theory.

The reason these arguments are first to be used, as well as ineffective, is that they start from the premise that institutionally those performing the surveillance are “the good guys”, and their aim is to catch “the bad guys” to protect the public. Sure, in the process mistakes happen, but they are in good faith and are rectified since all the good people are on the same side after all. “Bad apples” misusing their surveillance powers will be weeded out, since institutionally the context in which they use these powers is benevolent, and devoid of malice. On can easily see why privacy advocates in the UK have found it easy to use this assumption, since they mostly lobby politicians and have a close relationship with law enforcement as well as industry, who while admitting isolated mistakes will never admit a systematic privacy problem, let alone systematic malicious use of surveillance powers.

The tide is turning on this argument. In the recent months we have witnessed direct interference with the elected political process by the police, namely the raid on the Parliament office of MP Damian Green. As The Register reports “Green’s homes and offices were searched on 27 November following his arrest, on suspicion of leaking embarrassing informationfrom the Home Office.” The information was simply politically embarrassing, not sensitive or national security related. It seem this incident has challenged in the mainstream that those in charge of surveillance will simply act in the public interest, and other cases of mass political surveillance have since seen the light:

• First a company named The Consulting Association was found to keep an extensive database about construction workers, listing their trade union activity, past disputes with employers, and other sensitive personal information. It was providing a vetting service to the building industry to ensure that those active in the labour movement, basically do not get jobs.
• Secondly a Guardian investigation uncovered that the Metropolitan Police keeps a database of people attending protests, despite them never have been in trouble with the law, and specifically targets journalists covering protests. (The video is highly recommended.)

These are no more isolated abuses, but systematic operations running for many years, and supported at the highest level of management of both organizations. In its editorial the Guardianput its finger on the key argument against surveillance powers by finally saying out loud: “today’s revelations underline the perils surveillance represent for democracy [...]“. These worries are now being echoed at the highest echelons of the political system, as The Register reports regarding the Policing complaints at the recent Climate Camp:

“The problem with incidents of this kind, according to Norman Baker MP, who addressed the meeting on the Climate Camp protest yesterday is that they look suspiciously like police-made law and go hand in hand with the politicisation of the police. He said: “The IPCC exist to investigate allegations of individual misconduct by Police Officers. They are not there to investigate systemic abuses of power, which is what seem to be going on in cases such as the Climate Camp.”

“I am a strong supporter of the Police. But there looks increasingly to be a need for additional oversight into the ways in which they interpret the law.”