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Dan Boneh dabo@cs.stanford.edu Professor of Computer Science and Electrical Engineering, Stanford University. View Dan Boneh’s profile on LinkedIn, the world's largest professional community.

Professor Boneh received his Ph.D from Princeton University and joined Stanford in 1997. Verifiable Delay Functions. Slalom: Fast, Verifiable and Private Execution of Neural Networks in Trusted Hardware. Building upon a simple secure outsourcing scheme for matrix multiplication, we propose Slalom, a framework that outsources execution of all linear layers in a DNN from any trusted environment (e.g., SGX, TrustZone or Sanctum) to a faster co-located device. Professor Boneh's research focuses on applications of cryptography to computer security. It was created by Dan Boneh, Henry Corrigan-Gibbs (both at Stanford University) and Stuart Schechter Professor Boneh heads the applied cryptography group and co-direct the computer security lab. His work includes cryptosystems with novel properties, web security, security for mobile devices, and cryptanalysis. CV; Florian Tramèr. Dan Boneh, Joseph Bonneau, Benedikt Bunz, and Ben Fisch. As Machine Learning (ML) gets applied to security-critical or sensitive domains, there is a growing need for integrity and privacy guarantees for ML computations running in untrusted environments. This paper initiates the study of high performance execution of Deep Neural Networks (DNNs) in trusted environments by efficiently partitioning computations between trusted and untrusted devices. My advisor is Prof. Dan Boneh and I am part of the Applied Crypto Group. Professor Boneh's research focuses on applications of cryptography to computer security. A pragmatic solution comes from Trusted Execution Environments, which use hardware and software protections to isolate sensitive computations from the untrusted software stack.
International Conference on Learning Representations (ICLR), 2019. Mail: Computer Science Dept., Gates 475, Stanford, CA, 94305-9045 ; Office: CS Building, Gates 475. For two canonical DNNs, VGG16 and MobileNet, we obtain 20x and 6x increases in throughput for verifiable inference, and 10x and 3.5x for verifiable and private inference. In 2011 Dr. Boneh received the Ishii award for industry education innovation. The Applied Crypto Group is a part of the Security Lab in the Computer Science Department at Stanford University.Research projects in the group focus on various aspects of network and computer security. Address. I am a fourth year PhD student in Computer Science at Stanford University advised by Dan Boneh. I am grateful for the generous support of the Swiss National Science Foundation and the Open Philanthropy Project. Co-director of the Stanford Computer Security Lab. Florian Tramèr and Dan Boneh. • I … In particular the group focuses on applications of cryptography to real-world security problems. Obstacles to the Adoption of Secure Communication Tools. Find link is a tool written by Edward Betts.. searching for Dan Boneh 16 found (49 total) alternate case: dan Boneh Balloon hashing (249 words) exact match in snippet view article find links to article proven memory-hard password-hashing and modern design. My research interests lie in Computer Security, Machine Learning and Cryptography. In The 2018 IACR International Cryptology Conference, August 2018 Ruba Abu-Salma, M. Angela Sasse, Joseph Bonneau, Anastasia Danilova, Alena Naiakshina, and Matthew Smith. He is the author of over a hundred publications in the field and is a Packard and Alfred P. Sloan fellow. However, these isolation guarantees come at a price in performance, compared to untrusted alternatives.

We evaluate Slalom by executing DNNs in an Intel SGX enclave, which selectively outsources work to an untrusted GPU. His work includes cryptosystems with novel properties, web security, security for mobile devices, and cryptanalysis. He is the author of over a hundred publications in the field and is a Packard and Alfred P. Sloan fellow. Dan has 1 job listed on their profile. My CV • I am a third-year PhD Student in computer science at Stanford University. He is a recipient of the 2014 ACM prize and the 2013 Godel prize.

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