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Evasion Attacks on Cost-Utility-Based Adversarial Training for Online AutoML in IoT Networks
As Internet of Things (IoT) networks increasingly depend on machine learning for anomaly, malware, intrusion detection, and network monitoring, such systems have become attractive targets for evasion attacks. Evasion attacks pose a major security risk because an adversary intentionally modifies inpu
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