48 citations · 72 across the 8 of their papers we have counts for
3 papers · 1 filter
SkipFuzz: Active Learning-based Input Selection for Fuzzing Deep Learning Libraries
Hong Jin Kang, Pattarakrit Rattanukul, Stefanus Agus Haryono +4
Many modern software systems are enabled by deep learning libraries such as TensorFlow and PyTorch. As deep learning is now prevalent, the security of deep learning libraries is a…
Symbolic Execution for Deep Neural Networks
Divya Gopinath, Kaiyuan Wang, Mengshi Zhang +2
Deep Neural Networks (DNN) are increasingly used in a variety of applications, many of them with substantial safety and security concerns. This paper introduces DeepCheck, a new ap…
Badger: Complexity Analysis with Fuzzing and Symbolic Execution
Yannic Noller, Rody Kersten, Corina S. Păsăreanu
Hybrid testing approaches that involve fuzz testing and symbolic execution have shown promising results in achieving high code coverage, uncovering subtle errors and vulnerabilitie…