Arvind Narayanan is an Assistant Professor at Princeton's Department of Computer Science and Center for Information Technology Policy and an Affiliate Scholar at the Stanford Law School Center for Internet and Society. He studies information privacy and security, and has a side-interest in tech 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.
The Do Not Track war has raged for well over a year now. There are, broadly, two Do Not Track proposals: one chiefly backed by the ad industry, and another advanced by privacy advocates. These proposals reflect vastly different visions for Do Not Track with vastly different practical consequences. Read more » about The Trouble with ID Cookies: Why Do Not Track Must Mean Do Not Collect
A 1993 New Yorker cartoon famously proclaimed, "On the Internet, nobody knows you're a dog." The Web is a very different place today; you now leave countless footprints online. You log into websites. You share stuff on social networks. You search for information about yourself and your friends, family, and colleagues. And yet, in the debate about online tracking, ad networks and tracking companies would have you believe we're still in the early 90s — they regularly advance, and get away with, “anonymization” or “we don’t collect Personally Identifiable Information” as an answer to privacy concerns.
Joint post with Jonathan Mayer.
Earlier today Mozilla announced support for Do Not Fool, a proposed mechanism for opting out of April Fools' pranks. We cannot support this misguided effort.
First, Do Not Fool would require fundamentally reengineering the Internet, the HTTP protocol, and countless websites. Many of your favorite web destinations like The Onion rely on fooling. Read more » about Do Not Fool Will Make the Internet Explode
A frequent misconception of Do Not Track is that the goal is to prevent tracking by online advertisers. In fact, tracking is a much broader problem on the web, and our Do Not Track vision at Stanford, while principally aimed at "third-party" tracking, does not focus on specific industry segments. Barocas and Nissenbaum said it best: Read more » about Do Not Track isn't just about Behavioral Advertising
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). Read more » about Eternal vigilance is a solvable technology problem: A proposal for streamlined privacy alerts
"“There are very good reasons why we have legal and social institutions and economic intermediaries,” said Arvind Narayanan, an assistant professor of computer science at Princeton who studies block-chain technology. Read more » about Data Security Is Becoming the Sparkle in Bitcoin
"“A couple of us and our graduate students in the computer science department have been doing and publishing research on bitcoins, and it’s been a fascinating system, bringing together cryptography, distributive systems and game theory,” Narayanan said. “Bitcoins put them together in a way the academy has never anticipated.”" Read more » about U. faculty codevelop free online course on Bitcoin
""What's unfortunate is the huge gap of information - understanding what's happening on the Web and what users know about tracking," said conference organiser and assistant Professor of Computer Science Arvind Narayanan. "We're interested in building tools by the public and for the public. We want to make transparency mutually beneficial between businesses and Web users."" Read more » about Tracking the trackers: Investigators reveal pervasive profiling of web users
"Narayanan argued that game theorists who work in the bitcoin space need to do a better job of interfacing with other parts of the ecosystem in order to obtain more reliable data.
He said: “What I think is that the theorists and academics working on bitcoin need to work out to the community, the miners, and have a firm grasp of some of these strategies’ implications in order to input into the game theory models.”" Read more » about Bitcoin Miners Debate Risks and Rewards at Las Vegas Convention
""The original idea was to replace a variety of opt-out mechanisms with a browser preference," said Arvind Narayanan, a computer science professor at Princeton who worked with others on developing a standard around DNT. "But opt out of what? That's where there's disagreement," he said." Read more » about 'Do not track'? Oh what the heck, go ahead
Solutions to many pressing economic and societal challenges lie in better understanding data. New tools for analyzing disparate information sets, called Big Data, have revolutionized our ability to find signals amongst the noise. Big Data techniques hold promise for breakthroughs ranging from better health care, a cleaner environment, safer cities, and more effective marketing. Yet, privacy advocates are concerned that the same advances will upend the power relationships between government, business and individuals, and lead to prosecutorial abuse, racial or other profiling, discrimination, redlining, overcriminalization, and other restricted freedoms. Read more » about Big Data and Privacy: Making Ends Meet
View the full video on YouTube.
Talk by Arvind Narayanan at the University of Maryland.
Based on a paper-in-progress by Arvind Narayanan and Joseph Bonneau
Abstract: Behind the hype and tumult of the markets, researchers have been quietly producing a series of exciting results about Bitcoin and cryptocurrencies. In this paper we’ll explain why computer scientists should pay attention to these developments. Read more » about Why Bitcoin Matters (To Computer Scientists)