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Few-Shot Anti-Forgetting Intrusion Detection by 王紹睿 is a document available to read on EtoBox.

This document presents a few-shot and anti-forgetting network intrusion detection system based on online meta-learning, addressing the challenges of limited labeled samples and catastrophic forgetting in IoT environments. The proposed system utilizes Model-Agnostic Meta-Learning (MAML) to efficiently train models with scarce data while preserving previous models to combat forgetting. Experiments demonstrate that the system maintains strong performance over time, effectively adapting to new attack patterns w

Author

王紹睿

Language

EN