A Hybrid Deep Learning Model for Network Intrusion Detection System Using Seq2Seq and ConvLSTM-Subnets

A Hybrid Deep Learning Model for Network Intrusion Detection System Using Seq2Seq and ConvLSTM-Subnets

Network Intrusion Detection Systems (NIDS) are essential for identifying and mitigating malicious activities in network environments. As cyber threats evolve in complexity, traditional NIDSs often struggle to detect sophisticated attacks effectively, especially those involving intricate temporal and...

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Bibliographic Details
Main Authors: S. Hariharan, Y. Annie Jerusha, G. Suganeshwari, S. P. Syed Ibrahim, Uday Tupakula, Vijay Varadharajan
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Network intrusion detection
deep learning
Seq2Seq auto-encoders
hybrid architecture
LSTM
Online Access:https://ieeexplore.ieee.org/document/10883985/
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https://ieeexplore.ieee.org/document/10883985/

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