恶意软件顶会论文
DeepDi: Learning a Relational Graph Convolutional Network Model on Instructions for Fast and Accurate Disassembly https://www.usenix.org/conference/usenixsecurity22/presentation/yu-sheng
A Large-scale Temporal Measurement of Android Malicious Apps: Persistence, Migration, and Lessons Learned https://www.usenix.org/conference/usenixsecurity22/presentation/shen
Mining Node.js Vulnerabilities via Object Dependence Graph and Query https://www.usenix.org/conference/usenixsecurity22/presentation/li-song
Mistrust Plugins You Must: A Large-Scale Study Of Malicious Plugins In WordPress Marketplaces https://www.usenix.org/conference/usenixsecurity22/presentation/kasturi
Dos and Don'ts of Machine Learning in Computer Security https://www.usenix.org/conference/usenixsecurity22/presentation/arp
Expected Exploitability: Predicting the Development of Functional Vulnerability Exploits https://www.usenix.org/conference/usenixsecurity22/presentation/suciu
FUGIO: Automatic Exploit Generation for PHP Object Injection Vulnerabilities https://www.usenix.org/conference/usenixsecurity22/presentation/park-sunnyeo
RE-Mind: a First Look Inside the Mind of a Reverse Engineer https://www.usenix.org/conference/usenixsecurity22/presentation/mantovani
Towards Automatically Reverse Engineering Vehicle Diagnostic Protocols https://www.usenix.org/conference/usenixsecurity22/presentation/yu-le
Wobfuscator: Obfuscating JavaScript Malware via Opportunistic Translation to WebAssembly https://weihang-wang.github.io/papers/Wobfuscator-sp22.pdf
The Droid is in the Details: Environment-aware Evasion of Android Sandboxes
A Lightweight IoT Cryptojacking Detection Mechanism in Heterogeneous Smart Home Networks