Keisuke Nishimura, Yuichi Sugiyama, Yuki Koike, Masaya Motoda, Tomoya Kitagawa, Toshiki Takatera, Yuma Kurogome (Ricerca Security, Inc.)

Fuzzing has contributed to automatically identifying bugs and vulnerabilities in the software testing field. Although it can efficiently generate crashing inputs, these inputs are usually analyzed manually. Several root cause analysis (RCA) techniques have been proposed to automatically analyze the root causes of crashes to mitigate this cost. However, outstanding challenges for realizing more elaborate RCA techniques remain unknown owing to the lack of extensive evaluation methods over existing techniques. With this problem in mind, we developed an end-to-end benchmarking platform, RCABench, that can evaluate RCA techniques for various targeted programs in a detailed and comprehensive manner. Our experiments with RCABench indicated that the evaluations in previous studies were not enough to fully support their claims. Moreover, this platform can be leveraged to evaluate emerging RCA techniques by comparing them with existing techniques.

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Security Awareness Training through Experiencing the Adversarial Mindset

Jens Christian Dalgaard, Niek A. Janssen, Oksana Kulyuk, Carsten Schurmann (IT University of Copenhagen)

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Firefly: Spoofing Earth Observation Satellite Data through Radio Overshadowing

Edd Salkield, Sebastian Köhler, Simon Birnbach, Richard Baker (University of Oxford). Martin Strohmeier (armasuisse S+T), Ivan Martinovic (University of Oxford) Presenter: Edd Salkield

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PISE: Protocol Inference using Symbolic Execution and Automata Learning

Ron Marcovich, Orna Grumberg, Gabi Nakibly (Technion, Israel Institute of Technology)

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