1.3k citations · 2.7k across the 38 of their papers we have counts for
5 papers · 1 filter
Towards Practical Verification of Machine Learning: The Case of Computer Vision Systems
Kexin Pei, Linjie Zhu, Yinzhi Cao +3
Due to the increasing usage of machine learning (ML) techniques in security- and safety-critical domains, such as autonomous systems and medical diagnosis, ensuring correct behavio…
Tug-of-War: Observations on Unified Content Handling
Theofilos Petsios, Adrian Tang, Dimitris Mitropoulos +3
Modern applications and Operating Systems vary greatly with respect to how they register and identify different types of content. These discrepancies lead to exploits and inconsist…
SlowFuzz: Automated Domain-Independent Detection of Algorithmic Complexity Vulnerabilities
Theofilos Petsios, Jason Zhao, Angelos D. Keromytis +1
Algorithmic complexity vulnerabilities occur when the worst-case time/space complexity of an application is significantly higher than the respective average case for particular use…
DeepTest: Automated Testing of Deep-Neural-Network-driven Autonomous Cars
Yuchi Tian, Kexin Pei, Suman Jana +1
Recent advances in Deep Neural Networks (DNNs) have led to the development of DNN-driven autonomous cars that, using sensors like camera, LiDAR, etc., can drive without any human i…
DeepXplore: Automated Whitebox Testing of Deep Learning Systems
Kexin Pei, Yinzhi Cao, Junfeng Yang +1
Deep learning (DL) systems are increasingly deployed in safety- and security-critical domains including self-driving cars and malware detection, where the correctness and predictab…