Anomaly detection based on profile signature in network using machine learning technique

Kayvan Atefi, S. Yahya, Amirali Rezaei, Siti Hazyanti Binti Mohd Hashim
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引用次数: 9

Abstract

Within the last couple of years, a lot of IDSs have already been developed, both as research prototypes and as commercial systems. The aim of Intrusion Detection would be to positively identify all true attacks and adversely identify all non-attacks. Through the study of the procedure and signature of intrusion behaviors, IDS can produce a real-time reaction to intrusion occasions and invasion processes. The objective of this study is to work with appropriate algorithms for intrusion detection and hybrid them to find acceptable results and investigate on new hybrid techniques of intrusion detecting system with high accuracy. Moreover, it also aims to minimize a false positive and false negative alarms in networks.
基于特征签名的网络异常检测
在过去的几年里,已经开发出了许多ids,既有研究原型,也有商业系统。入侵检测的目的是积极地识别所有真正的攻击,消极地识别所有非攻击。入侵检测通过研究入侵行为的过程和特征,能够对入侵事件和入侵过程做出实时反应。本研究的目的是利用合适的入侵检测算法,并将它们混合起来以获得可接受的结果,并探索新的高精度入侵检测系统的混合技术。此外,它还旨在最大限度地减少网络中的假阳性和假阴性警报。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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