Dr. Vaibhav Garg is an Award Winning Executive who currently works as the Executive Director of Cybersecurity & Privacy Research and Public Policy Research at Comcast Cable. He has a PhD in Security Informatics from Indiana University and a M.S. in Information Security from Purdue University. He has more than 15 years of industry experience in domains that span Tech Policy, Cybersecurity, Privacy, AI, and Economics. He has co-authored over thirty peer reviewed publications and received the best paper award at the 2011 eCrime Researcher's Summit for his work on the economics of cybercrime. He previously served as the Editor in Chief of ACM Computers & Society, where he received the ACM SIGCAS Outstanding Service Award.

Dr. Garg currently serves as the Working Group Lead for the President’s National Security and Telecommunication’s Advisory Committee’s workstream on Post-Quantum Cryptography. He served as the Vice Chair for Consumer Technology Association’s WG on Cybersecurity and Privacy. He is the Co-Chair for Communication Sector Coordinating Council’s Emerging Technology Committee. His projects and papers have been referenced by the National Institute of Standards and Technology, Organization for Economic Co-operation and Development, National Security and Telecommunication’s Advisory Committee, and Financial Sector Information Sharing and Analysis Center. He has previously presented at events like Broadband Breakfast, Usenix Enigma, Usenix PEPR, Telecommunications Policy Research Conference, Hack the Capitol, and State of the Net.

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On the Realism of LiDAR Spoofing Attacks against Autonomous...

Takami Sato (University of California, Irvine), Ryo Suzuki (Keio University), Yuki Hayakawa (Keio University), Kazuma Ikeda (Keio University), Ozora Sako (Keio University), Rokuto Nagata (Keio University), Ryo Yoshida (Keio University), Qi Alfred Chen (University of California, Irvine), Kentaro Yoshioka (Keio University)

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Measuring the Prevalence of Password Manager Issues Using In-Situ...

Adryana Hutchinson (The George Washington University), Jinwei Tang (Clark University), Adam Aviv (The George Washington University), Peter Story (Clark University)

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DRAGON: Predicting Decompiled Variable Data Types with Learned Confidence...

Caleb Stewart, Rhonda Gaede, Jeffrey Kulick (University of Alabama in Huntsville)

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