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Randomized Prediction Games for Adversarial Machine Learning., , , , и . CoRR, (2016)Poster: Attacking Malware Classifiers by Crafting Gradient-Attacks that Preserve Functionality., , и . ACM Conference on Computer and Communications Security, стр. 2565-2567. ACM, (2019)Robustness-Congruent Adversarial Training for Secure Machine Learning Model Updates., , , , , , и . CoRR, (2024)Backdoor Learning Curves: Explaining Backdoor Poisoning Beyond Influence Functions., , , , , , и . CoRR, (2021)Domain Knowledge Alleviates Adversarial Attacks in Multi-Label Classifiers., , , , , , и . IEEE Trans. Pattern Anal. Mach. Intell., 44 (12): 9944-9959 (2022)Digital Investigation of PDF Files: Unveiling Traces of Embedded Malware., и . IEEE Secur. Priv., 17 (1): 63-71 (2019)Towards Adversarial Malware Detection: Lessons Learned from PDF-based Attacks., , и . ACM Comput. Surv., 52 (4): 78:1-78:36 (2019)Wild Patterns Reloaded: A Survey of Machine Learning Security against Training Data Poisoning., , , , , , , , , и . ACM Comput. Surv., 55 (13s): 294:1-294:39 (2023)Adversarial Biometric Recognition : A review on biometric system security from the adversarial machine-learning perspective., , , , и . IEEE Signal Process. Mag., 32 (5): 31-41 (2015)Functionality-Preserving Black-Box Optimization of Adversarial Windows Malware., , , , и . IEEE Trans. Inf. Forensics Secur., (2021)