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20202022
most citedPrivacy for All: Demystify Vulnerability Disparity of Differential Privacy against Membership Inference Attack

12 citations · 21 across the 5 of their papers we have counts for

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6 papers · 1 filter

cs.CR2024

SoK: Where's the "up"?! A Comprehensive (bottom-up) Study on the Security of Arm Cortex-M Systems

Xi Tan, Zheyuan Ma, Sandro Pinto +6

Arm Cortex-M processors are the most widely used 32-bit microcontrollers among embedded and Internet-of-Things devices. Despite the widespread usage, there has been little effort i…

cs.CR2022

Building Embedded Systems Like It's 1996

Ruotong Yu, Francesca Del Nin, Yuchen Zhang +6

Embedded devices are ubiquitous. However, preliminary evidence shows that attack mitigations protecting our desktops/servers/phones are missing in embedded devices, posing a signif…

cs.CR20211 cited

Towards Optimal Use of Exception Handling Information for Function Detection

Chengbin Pang, Ruotong Yu, Dongpeng Xu +3

Function entry detection is critical for security of binary code. Conventional methods heavily rely on patterns, inevitably missing true functions and introducing errors. Recently,…

cs.CR20207 cited

SoK: All You Ever Wanted to Know About x86/x64 Binary Disassembly But Were Afraid to Ask

Chengbin Pang, Ruotong Yu, Yaohui Chen +4

Disassembly of binary code is hard, but necessary for improving the security of binary software. Over the past few decades, research in binary disassembly has produced many tools a…

cs.CR2020

An Empirical Study on Benchmarks of Artificial Software Vulnerabilities

Sijia Geng, Yuekang Li, Yunlan Du +3

Recently, various techniques (e.g., fuzzing) have been developed for vulnerability detection. To evaluate those techniques, the community has been developing benchmarks of artifici…

cs.CR202012 cited

Privacy for All: Demystify Vulnerability Disparity of Differential Privacy against Membership Inference Attack

Bo Zhang, Ruotong Yu, Haipei Sun +3

Machine learning algorithms, when applied to sensitive data, pose a potential threat to privacy. A growing body of prior work has demonstrated that membership inference attack (MIA…