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When Your AI Becomes a Target: AI Security Incidents and Best Practices.

, , , , and . AAAI, page 23041-23046. AAAI Press, (2024)

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secml: Secure and explainable machine learning in Python., , , , , and . SoftwareX, (2022)A survey and experimental evaluation of image spam filtering techniques., , , and . Pattern Recognit. Lett., 32 (10): 1436-1446 (2011)FADER: Fast adversarial example rejection., , , , and . Neurocomputing, (2022)Poster: Attacking Malware Classifiers by Crafting Gradient-Attacks that Preserve Functionality., , and . ACM Conference on Computer and Communications Security, page 2565-2567. ACM, (2019)Denial-of-Service Attack on Object Detection Model Using Universal Adversarial Perturbation., , , , and . CoRR, (2022)Hardening RGB-D Object Recognition Systems against Adversarial Patch Attacks., , , , , , , , and . CoRR, (2023)Why Adversarial Reprogramming Works, When It Fails, and How to Tell the Difference., , , , , , , and . CoRR, (2021)Multimodal Anti-spoofing in Biometric Recognition Systems., , , , and . Handbook of Biometric Anti-Spoofing, Springer, (2014)Randomized Prediction Games for Adversarial Machine Learning., , , , and . CoRR, (2016)Robustness-Congruent Adversarial Training for Secure Machine Learning Model Updates., , , , , , and . CoRR, (2024)