R
Rui Qiao
Researcher at Stony Brook University
Publications - 7
Citations - 445
Rui Qiao is an academic researcher from Stony Brook University. The author has contributed to research in topics: Compiler & Instrumentation (computer programming). The author has an hindex of 7, co-authored 7 publications receiving 349 citations.
Papers
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Proceedings ArticleDOI
ANVIL: Software-Based Protection Against Next-Generation Rowhammer Attacks
Zelalem Birhanu Aweke,Salessawi Ferede Yitbarek,Rui Qiao,Reetuparna Das,Matthew Hicks,Yossi Oren,Todd Austin +6 more
TL;DR: A software-based defense, ANVIL, is developed, which thwarts all known rowhammer attacks on existing systems and is shown to be low-cost and robust, and experiments indicate that it is an effective approach for protecting existing and future systems from even advanced rowhAMmer attacks.
Proceedings ArticleDOI
A new approach for rowhammer attacks
Rui Qiao,Mark Seaborn +1 more
TL;DR: This paper proposes a new approach for rowhammer that is based on x86 non-temporal instructions and is much less constrained for a more challenging task: remote roWhammer attacks, i.e., triggering ro Whammer with existing, benign code.
Proceedings ArticleDOI
A platform for secure static binary instrumentation
TL;DR: A new platform for secure static binary instrumentation (PSI) is developed that overcomes these drawbacks of DBI techniques, while retaining the security, robustness and ease-of-use features.
Proceedings ArticleDOI
NORAX: Enabling Execute-Only Memory for COTS Binaries on AArch64
Yaohui Chen,Dongli Zhang,Ruowen Wang,Rui Qiao,Ahmed M. Azab,Long Lu,Hayawardh Vijayakumar,Wenbo Shen +7 more
TL;DR: The design and implementation of NORAX is presented, a practical system that retrofits XOM into stripped COTS binaries on AArch64 platforms and is designed to co-exist with other COTS binary hardening techniques, such as in-place randomization (IPR).
Proceedings ArticleDOI
Function Interface Analysis: A Principled Approach for Function Recognition in COTS Binaries
Rui Qiao,R. C. Sekar +1 more
TL;DR: This work combines a low-level technique for enumerating candidate functions with a novel static analysis for determining if these candidates exhibit the properties associated with a function interface, and achieves an F1-score above 99% across a broad range of programs across multiple languages and compilers.