S
Srinivas Devadas
Researcher at Massachusetts Institute of Technology
Publications - 498
Citations - 35003
Srinivas Devadas is an academic researcher from Massachusetts Institute of Technology. The author has contributed to research in topics: Sequential logic & Combinational logic. The author has an hindex of 88, co-authored 480 publications receiving 31897 citations. Previous affiliations of Srinivas Devadas include University of California, Berkeley & Cornell University.
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PUF Modeling Attacks on Simulated and Silicon Data.
Ulrich Rührmair,Jan Sölter,Frank Sehnke,Xiaolin Xu,Ahmed Mahmoud,Vera Stoyanova,Gideon Dror,Jürgen Schmidhuber,Wayne Burleson,Srinivas Devadas +9 more
TL;DR: In this article, numerical modeling attacks on several PUFs are discussed. But the authors focus on strong PUFs, and do not consider weak PUFs such as XOR Arbiter PUFs and Lightweight Secure PUFs.
Journal ArticleDOI
Identification and authentication of integrated circuits
TL;DR: Experiments show that the technique to reliably and securely identify individual integrated circuits (ICs) based on the precise measurement of circuit delays and a simple challenge–response protocol is viable, but that current implementations could require some strengthening before it can be considered as secure.
Journal ArticleDOI
Path ORAM: An Extremely Simple Oblivious RAM Protocol
Emil Stefanov,Marten van Dijk,Elaine Shi,T.-H. Hubert Chan,Christopher W. Fletcher,Ling Ren,Xiangyao Yu,Srinivas Devadas +7 more
TL;DR: It is formally proved that Path ORAM has a O(log N) bandwidth cost for blocks of size B = Ω (log2 N) bits, and is asymptotically better than the best-known ORAM schemes with small client storage.
Proceedings ArticleDOI
ISDL: an instruction set description language for retargetability
TL;DR: A tool is written that, given an ISDL description of a processor, automatically generates an assembler for it, and ongoing work includes the development of an automaticcode-generator generator.
Journal ArticleDOI
MUSTANG: state assignment of finite state machines targeting multilevel logic implementations
TL;DR: The authors present state-assignment algorithms that heuristically maximize the number of common cubes in the encoded network to maximize theNumber of literals in the resulting combinational logic network after multilevel logic optimization.