Survey of intrusion detection systems:techniques,datasets and challenges

作     者：Ansam Khraisat Iqbal Gondal Peter Vamplew Joarder Kamruzzaman 

作者机构：Internet Commerce Security LaboratoryFederation University AustraliaMount HelenAustralia 

出 版 物：《Cybersecurity》 (网络空间安全科学与技术（英文）)

年 卷 期：2018年第1卷第1期

页      面：12-33页

核心收录：

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：carried out within the Internet Commerce Security Lab which is funded by Westpac Banking Corporation 

主　　题：Malware Intrusion detection system NSL_KDD Anomaly detection Machine learning 

摘      要：Cyber-attacks are becoming more sophisticated and thereby presenting increasing challenges in accurately detecting *** to prevent the intrusions could degrade the credibility of security services,*** confidentiality,integrity,and *** intrusion detection methods have been proposed in the literature to tackle computer security threats,which can be broadly classified into Signature-based Intrusion Detection Systems(SIDS)and Anomaly-based Intrusion Detection Systems(AIDS).This survey paper presents a taxonomy of contemporary IDS,a comprehensive review of notable recent works,and an overview of the datasets commonly used for evaluation *** also presents evasion techniques used by attackers to avoid detection and discusses future research challenges to counter such techniques so as to make computer systems more secure.