3 papers
cs.SE2025
DynamiQ: Unlocking the Potential of Dynamic Task Allocation in Parallel Fuzzing
Wenqi Yan, Toby Murray, Benjamin I. P. Rubinstein +1
We present DynamiQ, a full-fledged and optimized successor to AFLTeam that supports dynamic and adaptive parallel fuzzing. Unlike most existing approaches that treat individual see…
cs.CR2025
Position: Certified Robustness Does Not (Yet) Imply Model Security
Andrew C. Cullen, Paul Montague, Sarah M. Erfani +1
While certified robustness is widely promoted as a solution to adversarial examples in Artificial Intelligence systems, significant challenges remain before these techniques can be…
cs.LG2025
Multi-level Certified Defense Against Poisoning Attacks in Offline Reinforcement Learning
Shijie Liu, Andrew C. Cullen, Paul Montague +2
Similar to other machine learning frameworks, Offline Reinforcement Learning (RL) is shown to be vulnerable to poisoning attacks, due to its reliance on externally sourced datasets…