Performance Evaluation of Intrusion Detection System Using Anomaly and Signature Based Algorithms to Reduction False Alarm Rate and Detect Unknown Attacks-Reference-Cited by-同舟云学术

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Performance Evaluation of Intrusion Detection System Using Anomaly and Signature Based Algorithms to Reduction False Alarm Rate and Detect Unknown Attacks

Published:2016-12 Issue: Volume: Page:
ISSN:
Container-title:2016 International Conference on Computational Science and Computational Intelligence (CSCI)
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Author:

Hussein Safwan Mawlood

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/7879541/7881293/07881496.pdf?arnumber=7881496

Cited by 11 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. Anomaly based detection for identifying R2L (remote to local) attacks using RNN-LSTM in comparison with DNN for reducing false alarm rate;AIP Conference Proceedings;2024

2. Enhancing intrusion detection recursive feature elimination with resampling in WSN;International Journal of System Assurance Engineering and Management;2023-10-19

3. Cyber Security Issues: Web Attack Investigation;Hybrid Intelligent Systems;2023

4. Effectiveness Evaluation of Different IDSs Using Integrated Fuzzy MCDM Model;Electronics;2022-03-09

5. A Vote-Based Architecture to Generate Classified Datasets and Improve Performance of Intrusion Detection Systems Based on Supervised Learning;Future Internet;2022-02-25

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