下一代网络入侵检测系统(NG-NIDS)

2021 15th International Conference on Advanced Technologies, Systems and Services in Telecommunications (TELSIKS) Pub Date : 2021-10-20 DOI:10.1109/TELSIKS52058.2021.9606424

Yazan Alnajjar, Jinane Mounsef

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引用次数: 0

摘要

本文介绍了基于人工神经网络(ANN)和机器学习(ML)算法的下一代智能网络入侵检测系统(NG-NIDS)。通过在良性流量和恶意流量上训练模型获得了结果。所提出的NG-NIDS检测恶意流量的准确率达到99.9%，体现了该设计的准确性和可靠性。

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Next-Generation Network Intrusion Detection System (NG-NIDS)

This paper introduces the Next-Generation Network Intrusion Detection System (NG-NIDS) with intelligent capabilities based on the Artificial Neural Networks (ANN) and Machine Learning (ML) algorithms. The results have been achieved by training the model on a benign as well as malicious traffic. The proposed NG-NIDS achieved 99.9% accuracy of detecting the malicious traffic, which reflects the fact that this design is accurate and reliable.

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2021 15th International Conference on Advanced Technologies, Systems and Services in Telecommunications (TELSIKS)

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