Sheng Yu (余晟)
PhD Candidate
Department of Computer Science
University of California, Riverside
email: syu061_at_ucr.edu
PhD Candidate
Department of Computer Science
University of California, Riverside
email: syu061_at_ucr.edu
I'm a Computer Science Ph.D. candidate at UC Riverside, advised by Prof. Heng Yin. I'm also working at Deepbits. My research interests mainly lie in Computer Security. I work on applying machine learning techniques in binary analysis, including reverse engineering, malware detection and analysis, vulnerability discovery, binary composition analysis, etc.
[DSN'24] Sheng Yu, Wei Song, Xunchao Hu, and Heng Yin, On the Correctness of Metadata-based SBOM Generation: A Differential Analysis Approach, to appear in the 54th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, June 2024.
[NDSS'24] Lian Gao, Yu Qu, Sheng Yu, Yue Duan, and Heng Yin, SigmaDiff: Semantics-Aware Deep Graph Matching for Pseudocode Diffing, in the Network and Distributed System Security Symposium, February 2024.
[USENIX Security'22] Sheng Yu, Yu Qu, Xunchao Hu, and Heng Yin, DeepDi: Learning a Relational Graph Convolutional Network Model on Instructions for Fast and Accurate Disassembly, in the 31st USENIX Security Symposium, August 2022.