Narayanan, Arvind2025-03-042025-03-042025-03-04https://hdl.handle.net/11299/270163Oral history for NSF projectThis oral history interview is sponsored by and a part of NSF 2202484 “Mining a Useable Past: Perspectives, Paradoxes, and Possibilities with Security and Privacy,” at the Charles Babbage Institute. The interview begins with Princeton Professor of Computer Science Arvind Narayanan recounting how his interests developed from his pre-college days, transitioning from mathematics to computer science. He majored in the latter at Indian Institute of Technology. Madras. He then went on to the University of Texas, Austin, to earn his Ph.D. in Computer Science. He discusses how his dissertation, broadly on deanonymization, was shaped by the mentorship of his advisor Vitaly Shmatikov. He relates his entrepreneurial efforts in Silicon Valley before returning to academia at Princeton in the Center for Information Technology Policy, which was then set up by Ed Felten. Narayanan comments on the state of technology policy broadly and how the topic was approached before the 2012 Menlo Reports. He discusses the privacy implications of the Fragile Families Challenge, a 2017 project partnering with Princeton’s Sociology Department. He explains how his approach as a cybersecurity researcher differed from the HCI community, by considering dark patterns deployed by adversaries. Amazon and Expedia were examples of e-commerce platforms utilizing these dark patterns. He also related experiences with Bitcoin, blockchain technology, and their communities. He shares his view of the past focus of computer security on malware and grayware as a possible future focus. He also offers his views on how enterprise systems differ from solely technical problems. Additionally, he discusses his approach to mentoring graduate students, his book project AI Snake Oil, and shares his perspectives on the open AI movement's similarity and differences from historical open-source software movements.en-USComputer history,privacysecurityUniversity of Austin-TexasSilicon ValleyNetflix datasetdeanonymizationtechnology policyPrinceton Universitysociologyriskdark patternsonline businesse-commerce platformsartificial intelligencecybersecuritygraywareOral history interview