基于人工神经网络的入侵检测系统

2017 IEEE 15th International Symposium on Applied Machine Intelligence and Informatics (SAMI) Pub Date : 1900-01-01 DOI:10.1109/SAMI.2017.7880294

N. Ádám, B. Madoš, A. Baláz, T. Pavlík

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引用次数: 11

摘要

网络入侵检测系统分为基于签名和基于异常两种。本文提出的入侵检测系统属于基于异常的神经网络入侵检测系统(NNIDS)。提出的NNIDS能够成功识别网络环境中习得的恶意活动。测试了SYN flood攻击，UDP flood攻击，nMap扫描攻击，以及非恶意通信。

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Artificial neural network based IDS

The Network Intrusion Detection Systems (NIDS) are either signature based or anomaly based. In this paper presented NIDS system belongs to anomaly based Neural Network Intrusion Detection System (NNIDS). The proposed NNIDS is able to successfully recognize learned malicious activities in a network environment. It was tested for the SYN flood attack, UDP flood attack, nMap scanning attack, and also for non-malicious communication.

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来源期刊

2017 IEEE 15th International Symposium on Applied Machine Intelligence and Informatics (SAMI)

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