Adaptive Defense: Zero-Day Attack Detection in NIDS With Deep Reinforcement Learning

Adaptive Defense: Zero-Day Attack Detection in NIDS With Deep Reinforcement Learning

Zero-Day attack detection in Network Intrusion Detection Systems (NIDS) refers to the ability to identify previously unseen attack patterns during testing without having been explicitly trained on those specific attacks, utilizing learned features from other known attacks. In this paper, we propose...

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Bibliographic Details
Main Authors: Khorshed Alam, Md Fahad Monir, Md Junayed Hossain, Mohammad Shorif Uddin, Md. Tarek Habib
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Zero-day attack detection
deep reinforcement learning
cybersecurity
network intrusion detection systems
internet
unseen attack generalization
Online Access:https://ieeexplore.ieee.org/document/11063272/
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https://ieeexplore.ieee.org/document/11063272/

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