382 citations · 582 across the 21 of their papers we have counts for
4 papers · 1 filter
Static Exploration of Taint-Style Vulnerabilities Found by Fuzzing
Bhargava Shastry, Federico Maggi, Fabian Yamaguchi +2
Taint-style vulnerabilities comprise a majority of fuzzer discovered program faults. These vulnerabilities usually manifest as memory access violations caused by tainted program in…
Yes, Machine Learning Can Be More Secure! A Case Study on Android Malware Detection
Ambra Demontis, Marco Melis, Battista Biggio +6
To cope with the increasing variability and sophistication of modern attacks, machine learning has been widely adopted as a statistically-sound tool for malware detection. However,…
Leveraging Flawed Tutorials for Seeding Large-Scale Web Vulnerability Discovery
Tommi Unruh, Bhargava Shastry, Malte Skoruppa +4
The Web is replete with tutorial-style content on how to accomplish programming tasks. Unfortunately, even top-ranked tutorials suffer from severe security vulnerabilities, such as…
Fraternal Twins: Unifying Attacks on Machine Learning and Digital Watermarking
Erwin Quiring, Daniel Arp, Konrad Rieck
Machine learning is increasingly used in security-critical applications, such as autonomous driving, face recognition and malware detection. Most learning methods, however, have no…