A critical review of intrusion detection systems in the internet of things:techniques,deployment strategy,validation strategy,attacks,public datasets and challenges  

作　　者：Ansam Khraisat Ammar Alazab 

机构地区：[1]Federation University Australia,Federation University Australia,Ballarat,Australia

出　　处：《Cybersecurity》2021年第1期251-277,共27页网络空间安全科学与技术（英文）

基　　金：the Internet Commerce Security Lab, whichis funded by Westpac Banking Corporation.

摘　　要：The Internet of Things(IoT)has been rapidly evolving towards making a greater impact on everyday life to large industrial systems.Unfortunately,this has attracted the attention of cybercriminals who made IoT a target of malicious activities,opening the door to a possible attack on the end nodes.To this end,Numerous IoT intrusion detection Systems(IDS)have been proposed in the literature to tackle attacks on the IoT ecosystem,which can be broadly classified based on detection technique,validation strategy,and deployment strategy.This survey paper presents a comprehensive review of contemporary IoT IDS and an overview of techniques,deployment Strategy,validation strategy and datasets that are commonly applied for building IDS.We also review how existing IoT IDS detect intrusive attacks and secure communications on the IoT.It also presents the classification of IoT attacks and discusses future research challenges to counter such IoT attacks to make IoT more secure.These purposes help IoT security researchers by uniting,contrasting,and compiling scattered research efforts.Consequently,we provide a unique IoT IDS taxonomy,which sheds light on IoT IDS techniques,their advantages and disadvantages,IoT attacks that exploit IoT communication systems,corresponding advanced IDS and detection capabilities to detect IoT attacks.

关 键 词：MALWARE Intrusion detection system IOT Anomaly detection Machine learning Deep learning Internet of things ATTACKS IoT security 

分 类 号：TP393.08[自动化与计算机技术—计算机应用技术]