28 citations · 102 across the 18 of their papers we have counts for
4 papers · 1 filter
An Empirical Study of Deep Learning Models for Vulnerability Detection
Benjamin Steenhoek, Md Mahbubur Rahman, Richard Jiles +1
Deep learning (DL) models of code have recently reported great progress for vulnerability detection. In some cases, DL-based models have outperformed static analysis tools. Althoug…
Dataflow Analysis-Inspired Deep Learning for Efficient Vulnerability Detection
Benjamin Steenhoek, Hongyang Gao, Wei Le
Deep learning-based vulnerability detection has shown great performance and, in some studies, outperformed static analysis tools. However, the highest-performing approaches use tok…
FuzzerAid: Grouping Fuzzed Crashes Based On Fault Signatures
Ashwin Kallingal Joshy, Wei Le
Fuzzing has been an important approach for finding bugs and vulnerabilities in programs. Many fuzzers deployed in industry run daily and can generate an overwhelming number of cras…
DeepStability: A Study of Unstable Numerical Methods and Their Solutions in Deep Learning
E. Kloberdanz, K. G. Kloberdanz, W. Le
Deep learning (DL) has become an integral part of solutions to various important problems, which is why ensuring the quality of DL systems is essential. One of the challenges of ac…