March 2, 2015

Arvind Narayanan is an Assistant Professor of Computer Science at Princeton, and an affiliated faculty member at the Center for Information Technology Policy. He was previously a post-doctoral fellow at the Stanford Computer Science department and a Junior Affiliate Scholar at the Stanford Law School Center for Internet and Society. He studies privacy from a multidisciplinary perspective, focusing on the intersection between technology, law and policy. His research has shown that data anonymization is broken in fundamental ways, for which he jointly received the 2008 Privacy Enhancing Technologies Award. He is one of the researchers behind the "Do Not Track" proposal. You can follow Arvind on Twitter at @random_walker and on Google+ here.

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Nine awesome Bitcoin projects at Princeton

As promised, here are the final project presentations from the Bitcoin and cryptocurrency technologies class I taught at Princeton. I encouraged students to build something real, rather than toy class projects, and they delivered. I hope you’ll find these presentations interesting and educational, and that you build on the work presented here (I’ve linked to the projects on GitHub if the code is available).

If you haven’t already, you should sign up for the online version of this class we’re teaching starting in a couple of weeks. The class will prepare you to do projects just like these.

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Sign up now for the Bitcoin and cryptocurrency technologies online course

At Princeton I taught a course on Bitcoin and cryptocurrency technologies during the semester that just ended. Joe Bonneau unofficially co-taught it with me. Based on student feedback and what we accomplished in the course, it was extremely successful. Next week I’ll post videos of all the final project presentations.

The course was based on a series of video lectures. We’re now offering these lectures free to the public, online, together with homeworks, programming assignments, and a textbook. We’ve heard from computer science students at various institutions as well as the Bitcoin community about the need for structured educational materials, and we’re excited to fill this need.

We’re using Piazza as our platform. Here’s the course page. To sign up, please fill out this (very short) form.

The first several book chapters are already available. The course starts February 16, and we’ll start making the videos available closer to that date (you’ll need to sign up to watch the videos). Each week there will be a Google hangout with that week’s lecturer. We’ll also answer questions on Piazza.

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Consensus in Bitcoin: One system, many models

At a technical level, the Bitcoin protocol is a clever solution to the consensus problem in computer science. The idea of consensus is very general — a number of participants together execute a computation to come to agreement about the state of the world, or a subset of it that they’re interested in.

Because of this generality, there are different methods for analyzing and proving things about such consensus protocols, coming from different areas of applied math and computer science. These methods use different languages and terminology and embody different assumptions and views. As a result, they’re not always consistent with each other. This is a recipe for confusion; often people disagree because they’ve implicitly assumed one world-view or another. In this post I’ll explain the two main sets of models that are used to analyze the security of consensus in Bitcoin.

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It’s time to bring Bitcoin and cryptocurrencies into the computer science curriculum

In the privacy technologies grad seminar that I taught last semester, Bitcoin proved to be the most popular topic among students. Two groups did very different and equally interesting final projects on Bitcoin and cryptocurrencies; more on that below.

More broadly, we’re seeing a huge demand for learning the computer science underlying Bitcoin, both at Princeton and elsewhere. But research papers on Bitcoin don’t make for great teaching materials. Identifying the core ideas, building them up in logical progression, and connecting them to other areas of computer science is a challenging task.

Over the summer, I teamed up with Joe Bonneau, Ed Felten, and Andrew Miller to do just that. We’ve produced a lecture series which will start going online soon. While we spend some time in the lectures on the specifics of Bitcoin, much of our discussion is about the underlying principles which apply to cryptocurrencies in general. Steven Goldfeder and other students are working with us to produce homeworks, programming assignments, and a textbook, which will together comprise a complete online course. We’ll announce it here when it launches.
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No silver bullet: De-identification still doesn’t work

Paul Ohm’s 2009 article Broken Promises of Privacy spurred a debate in legal and policy circles on the appropriate response to computer science research on re-identification techniques. In this debate, the empirical research has often been misunderstood or misrepresented. A new report by Ann Cavoukian and Daniel Castro is full of such inaccuracies, despite its claims of “setting the record straight.”

In a response to this piece, Ed Felten and I point out eight of our most serious points of disagreement with Cavoukian and Castro. The thrust of our arguments is that (i) there is no evidence that de-identification works either in theory or in practice and (ii) attempts to quantify its efficacy are unscientific and promote a false sense of security by assuming unrealistic, artificially constrained models of what an adversary might do. [Read more...]

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Encryption as protest

As a computer scientist who studies Privacy-Enhancing Technologies, I remember my surprise when I first learned that some groups of people view and use them very differently than I’m used to. In computer science, PETs are used for protecting anonymity or confidentiality, often via application of cryptography, and are intended to be bullet-proof against an adversary who is trying to breach privacy.

By contrast, Helen Nissenbaum and others have developed a political and ethical theory of obfuscation [1], “a strategy for individuals, groups or communities to hide; to protect themselves; to protest or enact civil disobedience, especially in the context of monitoring, aggregated analysis, and profiling..”  CV Dazzle and Ad Nauseam are good examples.

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Why King George III Can Encrypt

[This is a guest post by Wenley Tong, Sebastian Gold, Samuel Gichohi, Mihai Roman, and Jonathan Frankle, undergraduates in the Privacy Technologies seminar that I offered for the second time in Spring 2014. They did an excellent class project on the usability of email encryption.]

PGP and similar email encryption standards have existed since the early 1990s, yet even in the age of NSA surveillance and ubiquitous data-privacy concerns, we continue to send email in plain text.  Researchers have attributed this apparent gaping hole in our security infrastructure to a deceivingly simple source: usability.  Email encryption, although cryptographically straightforward, appears too complicated for laypeople to understand.  In our project, we aimed to understand why this problem has eluded researchers for well over a decade and expand the design space of possible solutions to this and similar challenges at the intersection of security and usability.

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The importance of anonymous cryptocurrencies

Recently I was part of a collaboration on Mixcoin, a set of proposals for improving Bitcoin’s anonymity. A natural question to ask is: why do this research? Before I address that, an even more basic question is whether or not Bitcoin is already anonymous. You may have seen back-and-forth arguments on this question. So which is it?

An analogy with Internet anonymity is useful. The Bitcoin protocol doesn’t require users to provide identities, just like the Internet Protocol doesn’t. This is what people usually mean when they say Bitcoin is anonymous. But that statement by itself tells us little. A meaningful answer cannot be found at the protocol level, but by analyzing the ecosystem of services that develop around the protocol. [*]

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Eternal vigilance is a solvable technology problem: A proposal for streamlined privacy alerts

Consider three recent news articles about online privacy:

  • Google+ added a new feature that shows view counts on everything you post, including your photos. It’s enabled by default, but if you don’t want to be part of the popularity contest, there’s a setting to turn it off.

  • There is a new privacy tool called XPrivacy for Android that protects you from apps that are hungry for your personal information (it does this by by feeding them fake data).

  • A new study reveals that several education technology providers have intrusive privacy policies. Students and parents might want to take this into account in making choices about online education services.

These are just a few examples of the dozens of articles that come out every month informing privacy-conscious users that they need to change some setting, install a tool, or otherwise take some action to protect their privacy. In particular, companies often release new features with permissive defaults and an opt-out setting. It seems that online privacy requires eternal vigilance.

Eternal vigilance is hard. Even as a privacy researcher I often miss privacy news that affects me; for the majority of people who don’t have as much time to devote to online privacy, the burden is just too much. But before concluding that the situation is hopeless, let’s ask if there’s a technological solution.

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Bitcoin hacks and thefts: The underlying reason

Emin Gün Sirer has a fascinating post about how the use of NoSQL caused technical failures that led to the demise of Bitcoin exchanges Flexcoin and Poloniex. But these are only the latest in a long line of hacks of exchanges, other services, and individuals; a wide variety of bugs have been implicated. This suggests that there’s some underlying reason why Bitcoiners keep building systems that get exploited. In this post I’ll examine why.

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