Development of Anomaly-Based Intrusion Detection Scheme Using Deep Learning in Data Network-Reference-Cited by-同舟云学术

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Development of Anomaly-Based Intrusion Detection Scheme Using Deep Learning in Data Network

Published:2021-07-06 Issue: Volume: Page:
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Container-title:2021 12th International Conference on Computing Communication and Networking Technologies (ICCCNT)
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Author:

Raju Deepanshu,Sawai Sakshi,Gavel Shashank,Raghuvanshi Ajay Singh

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9579467/9579470/09579510.pdf?arnumber=9579510

Cited by 5 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Cost-sensitive stacked long short-term memory with an evolutionary framework for minority class detection;Applied Soft Computing;2024-11

2. An enhanced strategy for minority class detection using bidirectional GRU employing penalized cross-entropy and self-attention mechanisms for imbalance network traffic;The European Physical Journal Plus;2024-06-17

3. Anomalous Network Packet Detection: A Review of Attacks, Datasets and Techniques;Lecture Notes in Networks and Systems;2024

4. Intrusion detection based on machine learning and statistical feature ranking techniques;2023 13th International Conference on Cloud Computing, Data Science & Engineering (Confluence);2023-01-19

5. Multi-scale Memory Residual Network Based Deep Learning Model for Network Traffic Anomaly Detection;Intelligent Computing and Networking;2023

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