Hanzala Afzaal
1 indexed paper
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126
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Crypto×1AI×1ML×1
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2026
Enhancing Autonomous Online Intrusion Detection for IoT with Balanced Learning, Reliable Pseudo-Labels, and Lightweight Architectures
This paper enhances an existing autonomous online Intrusion Detection System (AOC-IDS) for IoT by addressing class imbalance, pseudo-label reliability, and computational overhead, achieving significant accuracy gains while improving deployability.
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