8 citations · 13 across the 4 of their papers we have counts for
7 papers
Development of a Neural Network-Based Mathematical Operation Protocol for Embedded Hexadecimal Digits Using Neural Architecture Search (NAS)
Victor Robila, Kexin Pei, Junfeng Yang
It is beneficial to develop an efficient machine-learning based method for addition using embedded hexadecimal digits. Through a comparison between human-developed machine learning…
NeuDep: Neural Binary Memory Dependence Analysis
Kexin Pei, Dongdong She, Michael Wang +6
Determining whether multiple instructions can access the same memory location is a critical task in binary analysis. It is challenging as statically computing precise alias informa…
Trex: Learning Execution Semantics from Micro-Traces for Binary Similarity
Kexin Pei, Zhou Xuan, Junfeng Yang +2
Detecting semantically similar functions -- a crucial analysis capability with broad real-world security usages including vulnerability detection, malware lineage, and forensics --…
XDA: Accurate, Robust Disassembly with Transfer Learning
Kexin Pei, Jonas Guan, David Williams-King +2
Accurate and robust disassembly of stripped binaries is challenging. The root of the difficulty is that high-level structures, such as instruction and function boundaries, are abse…
Efficient Formal Safety Analysis of Neural Networks
Shiqi Wang, Kexin Pei, Justin Whitehouse +2
Neural networks are increasingly deployed in real-world safety-critical domains such as autonomous driving, aircraft collision avoidance, and malware detection. However, these netw…
NEUZZ: Efficient Fuzzing with Neural Program Smoothing
Dongdong She, Kexin Pei, Dave Epstein +3
Fuzzing has become the de facto standard technique for finding software vulnerabilities. However, even state-of-the-art fuzzers are not very efficient at finding hard-to-trigger so…