1 citations · 1 across the 5 of their papers we have counts for
6 papers
Psyzkaller: Learning from Historical and On-the-Fly Execution Data for Smarter Seed Generation in OS kernel Fuzzing
Boyu Liu, Yang Zhang, Liang Cheng +6
OS Kernel fuzzers such as Syzkaller often struggle to generate syscall sequences that respect intrinsic Syscall Dependency Relations (SDRs), resulting in seeds that either violate…
Automatic Generation of a Cryptography Misuse Taxonomy Using Large Language Models
Yang Zhang, Wenyi Ouyang, Yi Zhang +3
The prevalence of cryptographic API misuse (CAM) is compromising the effectiveness of cryptography and in turn the security of modern systems and applications. Despite extensive ef…
Statistical Invisibility of a Physical Attack on QRNGs After Randomness Extraction
Yi-Fan Chen, Dong Wang, Yi-Bo Zhao +3
Current prevailing designs of quantum random number generators (QRNGs) designs typically employ post-processing techniques to distill raw random data, followed by statistical verif…
Tea: Program Repair Using Neural Network Based on Program Information Attention Matrix
Wenshuo Wang, Chen Wu, Liang Cheng +1
The advance in machine learning (ML)-driven natural language process (NLP) points a promising direction for automatic bug fixing for software programs, as fixing a buggy program ca…
Fuzzing Based on Function Importance by Interprocedural Control Flow Graph
Wenshuo Wang, Liang Cheng, Yang Zhang
Coverage-based graybox fuzzer (CGF), such as AFL has gained great success in vulnerability detection thanks to its ease-of-use and bug-finding power. Since some code fragments such…
Optimizing seed inputs in fuzzing with machine learning
Liang Cheng, Yang Zhang, Yi Zhang +4
The success of a fuzzing campaign is heavily depending on the quality of seed inputs used for test generation. It is however challenging to compose a corpus of seed inputs that ena…