Within a few years of Bitcoin’s arrival, academic security researchers—and then companies like Chainalysis—began to tear gaping holes in the masks separating Bitcoin users’ addresses and their real-world identities. They could follow bitcoins on the blockchain as they moved from address to address until they reached one that could be tied to a known identity. In some cases, an investigator could learn someone’s Bitcoin addresses by transacting with them, the way an undercover narcotics agent might conduct a buy-and-bust. In other cases, they could trace a target’s coins to an account at a cryptocurrency exchange where financial regulations required users to prove their identity. A quick subpoena to the exchange from one of Chainalysis’ customers in law enforcement was then enough to strip away any illusion of Bitcoin’s anonymity.
Chainalysis had combined these techniques for de-anonymizing Bitcoin users with methods that allowed it to “cluster” addresses, showing that anywhere from dozens to millions of addresses sometimes belonged to a single person or organization. When coins from two or more addresses were spent in a single transaction, for instance, it revealed that whoever created that “multi-input” transaction must have control of both spender addresses, allowing Chainalysis to lump them into a single identity. In other cases, Chainalysis and its users could follow a “peel chain”—a process analogous to tracking a single wad of cash as a user repeatedly pulled it out, peeled off a few bills, and put it back in a different pocket. In those peel chains, bitcoins would be moved out of one address as a fraction was paid to a recipient and then the remainder returned to the spender at a “change” address. Distinguishing those change addresses could allow an investigator to follow a sum of money as it hopped from one address to the next, charting its path through the noise of Bitcoin’s blockchain.
Thanks to tricks like these, Bitcoin had turned out to be practically the opposite of untraceable: a kind of honeypot for crypto criminals that had, for years, dutifully and unerasably recorded evidence of their dirty deals. By 2017, agencies like the FBI, the Drug Enforcement Agency, and the IRS’s Criminal Investigation division (or IRS-CI) had traced Bitcoin transactions to carry out one investigative coup after another, very often with the help of Chainalysis.
Entries Tagged "tracing"
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I was quoted in BuzzFeed:
“My problem with contact tracing apps is that they have absolutely no value,” Bruce Schneier, a privacy expert and fellow at the Berkman Klein Center for Internet & Society at Harvard University, told BuzzFeed News. “I’m not even talking about the privacy concerns, I mean the efficacy. Does anybody think this will do something useful? … This is just something governments want to do for the hell of it. To me, it’s just techies doing techie things because they don’t know what else to do.”
I haven’t blogged about this because I thought it was obvious. But from the tweets and emails I have received, it seems not.
This is a classic identification problem, and efficacy depends on two things: false positives and false negatives.
- False positives: Any app will have a precise definition of a contact: let’s say it’s less than six feet for more than ten minutes. The false positive rate is the percentage of contacts that don’t result in transmissions. This will be because of several reasons. One, the app’s location and proximity systems—based on GPS and Bluetooth—just aren’t accurate enough to capture every contact. Two, the app won’t be aware of any extenuating circumstances, like walls or partitions. And three, not every contact results in transmission; the disease has some transmission rate that’s less than 100% (and I don’t know what that is).
- False negatives: This is the rate the app fails to register a contact when an infection occurs. This also will be because of several reasons. One, errors in the app’s location and proximity systems. Two, transmissions that occur from people who don’t have the app (even Singapore didn’t get above a 20% adoption rate for the app). And three, not every transmission is a result of that precisely defined contact—the virus sometimes travels further.
Assume you take the app out grocery shopping with you and it subsequently alerts you of a contact. What should you do? It’s not accurate enough for you to quarantine yourself for two weeks. And without ubiquitous, cheap, fast, and accurate testing, you can’t confirm the app’s diagnosis. So the alert is useless.
Similarly, assume you take the app out grocery shopping and it doesn’t alert you of any contact. Are you in the clear? No, you’re not. You actually have no idea if you’ve been infected.
The end result is an app that doesn’t work. People will post their bad experiences on social media, and people will read those posts and realize that the app is not to be trusted. That loss of trust is even worse than having no app at all.
It has nothing to do with privacy concerns. The idea that contact tracing can be done with an app, and not human health professionals, is just plain dumb.
EDITED TO ADD: This Brookings essay makes much the same point.
EDITED TO ADD: This post has been translated into Spanish.
Google and Apple have announced a joint project to create a privacy-preserving COVID-19 contact tracing app. (Details, such as we have them, are here.) It’s similar to the app being developed at MIT, and similar to others being described and developed elsewhere. It’s nice seeing the privacy protections; they’re well thought out.
I was going to write a long essay about the security and privacy concerns, but Ross Anderson beat me to it. (Note that some of his comments are UK-specific.)
First, it isn’t anonymous. Covid-19 is a notifiable disease so a doctor who diagnoses you must inform the public health authorities, and if they have the bandwidth they call you and ask who you’ve been in contact with. They then call your contacts in turn. It’s not about consent or anonymity, so much as being persuasive and having a good bedside manner.
I’m relaxed about doing all this under emergency public-health powers, since this will make it harder for intrusive systems to persist after the pandemic than if they have some privacy theater that can be used to argue that the whizzy new medi-panopticon is legal enough to be kept running.
Second, contact tracers have access to all sorts of other data such as public transport ticketing and credit-card records. This is how a contact tracer in Singapore is able to phone you and tell you that the taxi driver who took you yesterday from Orchard Road to Raffles has reported sick, so please put on a mask right now and go straight home. This must be controlled; Taiwan lets public-health staff access such material in emergencies only.
Third, you can’t wait for diagnoses. In the UK, you only get a test if you’re a VIP or if you get admitted to hospital. Even so the results take 1-3 days to come back. While the VIPs share their status on twitter or facebook, the other diagnosed patients are often too sick to operate their phones.
Fourth, the public health authorities need geographical data for purposes other than contact tracing – such as to tell the army where to build more field hospitals, and to plan shipments of scarce personal protective equipment. There are already apps that do symptom tracking but more would be better. So the UK app will ask for the first three characters of your postcode, which is about enough to locate which hospital you’d end up in.
Fifth, although the cryptographers – and now Google and Apple – are discussing more anonymous variants of the Singapore app, that’s not the problem. Anyone who’s worked on abuse will instantly realise that a voluntary app operated by anonymous actors is wide open to trolling. The performance art people will tie a phone to a dog and let it run around the park; the Russians will use the app to run service-denial attacks and spread panic; and little Johnny will self-report symptoms to get the whole school sent home.
To me, the real problems aren’t around privacy and security. The efficacy of any app-based contact tracing is still unproven. A “contact” from the point of view of an app isn’t the same as an epidemiological contact. And the ratio of infections to contacts is high. We would have to deal with the false positives (being close to someone else, but separated by a partition or other barrier) and the false negatives (not being close to someone else, but contracting the disease through a mutually touched object). And without cheap, fast, and accurate testing, the information from any of these apps isn’t very useful. So I agree with Ross that this is primarily an exercise in that false syllogism: Something must be done. This is something. Therefore, we must do it. It’s techies proposing tech solutions to what is primarily a social problem.
EDITED TO ADD: Susan Landau on contact tracing apps and how they’re being oversold. And Farzad Mostashari, former coordinator for health IT at the Department of Health and Human Services, on contact tracing apps.
As long as 1) every contact does not result in an infection, and 2) a large percentage of people with the disease are asymptomatic and don’t realize they have it, I can’t see how this sort of app is valuable. If we had cheap, fast, and accurate testing for everyone on demand…maybe. But I still don’t think so.
EDITED TO ADD (4/15): More details from Apple and Google.
EDITED TO ADD (4/19): Apple and Google have strengthened the security and privacy of their system.
Researchers have exploited a flaw in the cryptocurrency Monero to break the anonymity of transactions.
EDITED TO ADD (4/13): Brad Tempelton wrote about this years ago.
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.
I’ve been asked this question by countless reporters in the past couple of weeks. Here’s a good explanation. Shorter answer: it’s easy to spoof source destination, and it’s easy to hijack unsuspecting middlemen and use them as proxies.
No, mandating attribution won’t solve the problem. Any Internet design will necessarily include anonymity.
This is impressive, and scary:
Every computer connected to the web has an internet protocol (IP) address, but there is no simple way to map this to a physical location. The current best system can be out by as much as 35 kilometres.
Now, Yong Wang, a computer scientist at the University of Electronic Science and Technology of China in Chengdu, and colleagues at Northwestern University in Evanston, Illinois, have used businesses and universities as landmarks to achieve much higher accuracy.
These organisations often host their websites on servers kept on their premises, meaning the servers’ IP addresses are tied to their physical location. Wang’s team used Google Maps to find both the web and physical addresses of such organisations, providing them with around 76,000 landmarks. By comparison, most other geolocation methods only use a few hundred landmarks specifically set up for the purpose.
The new method zooms in through three stages to locate a target computer. The first stage measures the time it takes to send a data packet to the target and converts it into a distance—a common geolocation technique that narrows the target’s possible location to a radius of around 200 kilometres.
Wang and colleagues then send data packets to the known Google Maps landmark servers in this large area to find which routers they pass through. When a landmark machine and the target computer have shared a router, the researchers can compare how long a packet takes to reach each machine from the router; converted into an estimate of distance, this time difference narrows the search down further. “We shrink the size of the area where the target potentially is,” explains Wang.
Finally, they repeat the landmark search at this more fine-grained level: comparing delay times once more, they establish which landmark server is closest to the target. The result can never be entirely accurate, but it’s much better than trying to determine a location by converting the initial delay into a distance or the next best IP-based method. On average their method gets to within 690 metres of the target and can be as close as 100 metres—good enough to identify the target computer’s location to within a few streets.
Interesting research: “One Bad Apple Spoils the Bunch: Exploiting P2P Applications to Trace and Profile Tor Users“:
Abstract: Tor is a popular low-latency anonymity network. However, Tor does not protect against the exploitation of an insecure application to reveal the IP address of, or trace, a TCP stream. In addition, because of the linkability of Tor streams sent together over a single circuit, tracing one stream sent over a circuit traces them all. Surprisingly, it is unknown whether this linkability allows in practice to trace a significant number of streams originating from secure (i.e., proxied) applications. In this paper, we show that linkability allows us to trace 193% of additional streams, including 27% of HTTP streams possibly originating from “secure” browsers. In particular, we traced 9% of Tor streams carried by our instrumented exit nodes. Using BitTorrent as the insecure application, we design two attacks tracing BitTorrent users on Tor. We run these attacks in the wild for 23 days and reveal 10,000 IP addresses of Tor users. Using these IP addresses, we then profile not only the BitTorrent downloads but also the websites visited per country of origin of Tor users. We show that BitTorrent users on Tor are over-represented in some countries as compared to BitTorrent users outside of Tor. By analyzing the type of content downloaded, we then explain the observed behaviors by the higher concentration of pornographic content downloaded at the scale of a country. Finally, we present results suggesting the existence of an underground BitTorrent ecosystem on Tor.
Definitely strange bedfellows:
A United Nations agency is quietly drafting technical standards, proposed by the Chinese government, to define methods of tracing the original source of Internet communications and potentially curbing the ability of users to remain anonymous.
The U.S. National Security Agency is also participating in the “IP Traceback” drafting group, named Q6/17, which is meeting next week in Geneva to work on the traceback proposal. Members of Q6/17 have declined to release key documents, and meetings are closed to the public.
A second, apparently leaked ITU document offers surveillance and monitoring justifications that seem well-suited to repressive regimes:
A political opponent to a government publishes articles putting the government in an unfavorable light. The government, having a law against any opposition, tries to identify the source of the negative articles but the articles having been published via a proxy server, is unable to do so protecting the anonymity of the author.
This is being sold as a way to go after the bad guys, but it won’t help. Here’s Steve Bellovin on that issue:
First, very few attacks these days use spoofed source addresses; the real IP address already tells you where the attack is coming from. Second, in case of a DDoS attack, there are too many sources; you can’t do anything with the information. Third, the machine attacking you is almost certainly someone else’s hacked machine and tracking them down (and getting them to clean it up) is itself time-consuming.
TraceBack is most useful in monitoring the activities of large masses of people. But of course, that’s why the Chinese and the NSA are so interested in this proposal in the first place.
It’s hard to figure out what the endgame is; the U.N. doesn’t have the authority to impose Internet standards on anyone. In any case, this idea is counter to the U.N. Universal Declaration of Human Rights, Article 19: “Everyone has the right to freedom of opinion and expression; this right includes freedom to hold opinions without interference and to seek, receive and impart information and ideas through any media and regardless of frontiers.” In the U.S., it’s counter to the First Amendment, which has long permitted anonymous speech. On the other hand, basic human and constitutional rights have been jettisoned left and right in the years after 9/11; why should this be any different?
But when the Chinese government and the NSA get together to enhance their ability to spy on us all, you have to wonder what’s gone wrong with the world.
Taser—yep, that’s the company’s name as well as the product’s name—is now selling a personal-use version of their product. It’s called the Taser C2, and it has an interesting embedded identification technology. Whenever the weapon is fired, it also sprays some serial-number bar-coded confetti, so a firing can be traced to a weapon and—presumably—the owner.
Anti-Felon Identification (AFID)
A system to deter misuse through enhanced accountability, AFID includes bar-coded serialization of each cartridge and disperses confetti-like ID tags upon activation.
Sidebar photo of Bruce Schneier by Joe MacInnis.