Ben Livshits is a researcher at Microsoft Research  in Redmond, WA and an affiliate professor at the University of Washington. Originally from St. Petersburg, Russia,he received a bachelor's degree in Computer Science and Math from Cornell University in 1999, and his M.S. and Ph.D. in Computer Science from Stanford University in 2002 and 2006, respectively. Dr. Livshits' research interests include application of sophisticated static and dynamic analysis techniques to finding errors in programs.

Ben has published papers at PLDI, POPL, Oakland Security, Usenix Security, CCS, SOSP, ICSE, FSE,and many other venues. He is known for his work in software reliability  and especially tools to improve software security, with a primary focus  on approaches to finding buffer overruns in C programs and a variety of security vulnerabilities(cross-site scripting,SQL injections,etc.)in Web-based applications. He is the author of several dozen academic papers and patents. Lately he has been focusing on how Web 2.0 application and browser reliability,performance,and security can be improved through a combination of static and runtime techniques. Ben generally does not speak of himself in the third person.

AG 1, AG 2, AG 3, AG 4, AG 5, SWS, RG1, MMCI   Info

English

60 Minutes

Saarbrücken

RePriv, the subject of our recent paper at Oakland S&P, is a browser-based technology that allows for Web personalization, while controlling the release of private information within the browser. We demonstrate how to perform mining of core user interests within a browser. We show that RePriv's default in-browser mining can be done with no noticeable overhead to normal browsing, and that the results it produces converge quickly. We then go on to show similar results for each of our case studies: that RePriv enables high-quality personalization, and that the performance impact each case has on the browser is minimal. We conclude that personalized content and individual privacy on the Web are not mutually exclusive.

While the focus of RePriv is on the browser, more recently, we have also introduced privacy-preserving personalization to mobile devices, by modifying the Windows Phone OS, with exciting results. The user in MoRePriv is classified into one of several profiles called personas. We will describe how MoRePriv applies to both legacy apps through automatic personalization and new phone apps by the operating system exposing personalization APIs.

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CISPA; Personalization and Privacy; Browser and Mobile; Dr. Maffei; Ben Livshits