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Dec 20, 2023 · We propose and evaluate a framework for adaptively optimizing black-box attacks and defenses against each other through the competitive game ...
We propose and evaluate a framework for adaptively optimizing black-box attacks and defenses against each other through the competitive game they form. To ...
Adversarial Markov Games. The most compelling threat for deployed ML sys- tems are hard-label, decision-based attacks like Bound- ary Attack [6], HSJA [10] ...
We propose and evaluate a framework for adaptively optimizing black-box attacks and defenses against each other through the competitive game ...
Bibliographic details on Adversarial Markov Games: On Adaptive Decision-Based Attacks and Defenses.
Adversarial Markov Games: On Adaptive Decision-Based Attacks and Defenses. I Tsingenopoulos, V Rimmer, D Preuveneers, F Pierazzi, L Cavallaro, ... arXiv ...
Dec 24, 2023 · Despite considerable efforts on making them robust, real-world ML-based systems remain vulnerable to decision based attacks, as definitive ...
Adversarial Markov Games: On Adaptive Decision-Based Attacks and Defenses. I Tsingenopoulos, V Rimmer, D Preuveneers, F Pierazzi, L Cavallaro, ... arXiv ...
Apr 10, 2024 · ... Adaptive Decision-Based Attacks and Defenses , In Extended abstract ... Adversarial Markov Games: On Adaptive Decision-Based Attacks and Defenses ...
2022. Adversarial Markov Games: On Adaptive Decision-Based Attacks and Defenses. I Tsingenopoulos, V Rimmer, D Preuveneers, F Pierazzi, L Cavallaro, ... arXiv ...