LEoNIDS: A Low-Latency and Energy-Efficient Network-Level Intrusion Detection System

Author:

Tsikoudis Nikos,Papadogiannakis Antonis,Markatos Evangelos P.

Funder

GCC funded by the Prevention of and Fight against Crime Programme of the European Commission—Directorate-General Home Affairs

FP7 Project SysSec through the European Commission

FORTH-ICS

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Science Applications,Human-Computer Interaction,Information Systems,Computer Science (miscellaneous)

Cited by 32 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. Measuring Throughput and Latency of Machine Learning Techniques for Intrusion Detection;Handbook of Research on AI and ML for Intelligent Machines and Systems;2023-11-27

2. Auto-Scaling Containerized Applications in Geo-Distributed Clouds;IEEE Transactions on Services Computing;2023-11

3. Research on Network Intrusion Simulation and Adversarial Strategies Based on Generate Adversarial Networks;Proceedings of the 8th International Conference on Cyber Security and Information Engineering;2023-09-22

4. Remediation technologies for contaminated groundwater due to arsenic (As), mercury (Hg), and/or fluoride (F): A critical review and way forward to contribute to carbon neutrality;Separation and Purification Technology;2023-06

5. Estimating Overhead Performance of Supervised Machine Learning Algorithms for Intrusion Detection;International Journal of Information Technologies and Systems Approach;2023-02-03

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