Adversarial RL for Port-Scan Evasion: Attacker Feature Visibility in Edge-Deployed IDS

Machine learning-based intrusion detection systems IDS are increasingly used in resource-constrained Internet of Things IoT environments, yet their robustness is often evaluated against static attacks rather than adversaries that adapt to detection feedback. This paper investigates adaptive...

Cybersecurity in Edge Computing: A Trust-Aware Federated Hybrid Intrusion Detection Framework

Edge computing has emerged as a critical computing paradigm in modern distributed systems by migrating data processing closer to end users and Internet of Things IoT devices. While this paradigm decentralizes processes, minimizes latency, and reduces backhaul bandwidth congestion, it exponentiall...