L
Lan Gao
Researcher at University of California, Riverside
Publications - 7
Citations - 379
Lan Gao is an academic researcher from University of California, Riverside. The author has contributed to research in topics: Encryption & Cryptography. The author has an hindex of 5, co-authored 7 publications receiving 367 citations. Previous affiliations of Lan Gao include VMware.
Papers
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Proceedings ArticleDOI
Fast secure processor for inhibiting software piracy and tampering
Jun Yang,Youtao Zhang,Lan Gao +2 more
TL;DR: This paper presents an innovative technique in which the cryptography computation is shifted off from thememory access critical path, namely "one-time pad" encryption, which improves the execution speed of the XOM architecture by 34.7% at maximum.
Journal ArticleDOI
Improving memory encryption performance in secure processors
Jun Yang,Lan Gao,Youtao Zhang +2 more
TL;DR: In this article, a pseudo-one-time pad encryption scheme was proposed to produce the instructions and data ciphertext in parallel with memory accesses, minimizing the trade-off between storage size and performance penalty.
Proceedings ArticleDOI
SENSS: security enhancement to symmetric shared memory multiprocessors
TL;DR: This paper develops a scheme that utilizes the cipher block chaining mode of the advanced encryption standard (CBC-AES) to achieve ultra low latency for the shared bus encryption and decryption and develops techniques to ensure the cryptographic computation throughput meets the high bandwidth of gigabyte buses.
Proceedings ArticleDOI
A low-cost memory remapping scheme for address bus protection
TL;DR: A lightweight solution to alleviating the pressure on the memory of side-channel attacks by reducing the memory traffic by a factor of 10 compared with the prior scheme, while keeping almost the same page fault rate as a baseline system with no security protection.
Journal ArticleDOI
Architectural support for protecting user privacy on trusted processors
TL;DR: The threat model to user privacy is identified and a new scheme for user privacy protection is proposed that effectively protects user privacy and only introduces very low overhead.