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Efficient Black-box Optimization of Adversarial Windows Malware with Constrained Manipulations., , , , and . CoRR, (2020)A Survey on Reinforcement Learning Security with Application to Autonomous Driving., , , , , , , and . CoRR, (2022)Nebula: Self-Attention for Dynamic Malware Analysis., , , and . CoRR, (2023)Robust Machine Learning for Malware Detection over Time., , , and . ITASEC, volume 3260 of CEUR Workshop Proceedings, page 169-180. CEUR-WS.org, (2022)Explaining Vulnerabilities of Deep Learning to Adversarial Malware Binaries., , , , and . ITASEC, volume 2315 of CEUR Workshop Proceedings, CEUR-WS.org, (2019)Detecting Attacks Against Deep Reinforcement Learning for Autonomous Driving., , , , , , and . ICMLC, page 57-62. IEEE, (2023)Adversarial EXEmples: A Survey and Experimental Evaluation of Practical Attacks on Machine Learning for Windows Malware Detection., , , , , and . CoRR, (2020)AI Security and Safety: The PRALab Research Experience., , , , , , , , and . Ital-IA, volume 3486 of CEUR Workshop Proceedings, page 324-328. CEUR-WS.org, (2023)Raze to the Ground: Query-Efficient Adversarial HTML Attacks on Machine-Learning Phishing Webpage Detectors., , , , , and . AISec@CCS, page 233-244. ACM, (2023)Living-off-The-Land Reverse-Shell Detection by Informed Data Augmentation., , , and . CoRR, (2024)