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
"Assuming an adversary, whether a criminal or intelligence agency, has a presence on the network, the working premise here is that the first- and third-party cookies dropped by sites and advertisers can be used to tie a user to web traffic without having to worry about dynamic IP addresses,” said the paper, “Cookies that give you away: Evaluating the surveillance implications of web tacking,” written by Dillon Reisman, Steven Englehardt, Christian Eubank, Peter Zimmerman, and Arvind Narayanan." Read more » about Connecting the Dots Between Cookies and Identities
"(Narayanan, elsewhere, in talking about his doctoral research on problems with data anonymization, said his thesis, "in a sentence, is that the level of anonymity that consumers expect—and companies claim to provide—in published or outsourced databases is fundamentally unrealizable.")" Read more » about Scientists explore safeguards for genomic data privacy
"Computer science professor Arvind Narayanan, one of the professors leading the project, said he believes Bitcoin provides an opportunity to decentralize prediction markets from external oversight." Read more » about U. researchers develop Bitcoin prediction market
Arvind Narayanan’s business card is an exercise in brevity. It contains no data except his name and the words “Google me,” a fitting calling card for an academic who specializes in privacy and anonymity research. When you do Google him, his online footprint is robust, but highly selective and pruned. Read more » about World's Most Wired Computer Scientist
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