Y. Li et al., “V-Fuzz: Vulnerability-Oriented Evolutionary Fuzzing” […we design and implement a vulnerability-oriented evolutionary fuzzing prototype named V-Fuzz, which aims to find bugs efficiently and quickly in a limited time…]https://t.co/J4WuZ7RPTS
— Arrigo Triulzi (@cynicalsecurity) January 15, 2019
https://arxiv.org/abs/1901.01142
J. Wang et al., “Superion: Grammar-Aware Greybox Fuzzing” […we propose a grammar-aware coverage-based greybox fuzzing approach to fuzz programs that process structured inputs…]https://t.co/6kOSnjkpLc
— Arrigo Triulzi (@cynicalsecurity) January 15, 2019
https://arxiv.org/abs/1812.01197
V. Manes et al., “Fuzzing: Art, Science, and Engineering” […To help preserve and bring coherence to the vast literature of fuzzing, this paper presents a unified, general-purpose model of fuzzing together with a taxonomy of the current literature…]https://t.co/cw98uPLKjB
— Arrigo Triulzi (@cynicalsecurity) January 15, 2019
https://arxiv.org/abs/1812.00140
Firmware Security 