Anomaly Detection for Industrial Internet of Things Cyberattacks  

作　　者：Rehab Alanazi Ahamed Aljuhani 

机构地区：[1]College of Computing and Information Technology,University of Tabuk,Tabuk,71491,Saudi Arabia

出　　处：《Computer Systems Science & Engineering》2023年第3期2361-2378,共18页计算机系统科学与工程（英文）

摘　　要：The evolution of the Internet of Things(IoT)has empowered modern industries with the capability to implement large-scale IoT ecosystems,such as the Industrial Internet of Things(IIoT).The IIoT is vulnerable to a diverse range of cyberattacks that can be exploited by intruders and cause substantial reputational andfinancial harm to organizations.To preserve the confidentiality,integrity,and availability of IIoT networks,an anomaly-based intrusion detection system(IDS)can be used to provide secure,reliable,and efficient IIoT ecosystems.In this paper,we propose an anomaly-based IDS for IIoT networks as an effective security solution to efficiently and effectively overcome several IIoT cyberattacks.The proposed anomaly-based IDS is divided into three phases:pre-processing,feature selection,and classification.In the pre-processing phase,data cleaning and nor-malization are performed.In the feature selection phase,the candidates’feature vectors are computed using two feature reduction techniques,minimum redun-dancy maximum relevance and neighborhood components analysis.For thefinal step,the modeling phase,the following classifiers are used to perform the classi-fication:support vector machine,decision tree,k-nearest neighbors,and linear discriminant analysis.The proposed work uses a new data-driven IIoT data set called X-IIoTID.The experimental evaluation demonstrates our proposed model achieved a high accuracy rate of 99.58%,a sensitivity rate of 99.59%,a specificity rate of 99.58%,and a low false positive rate of 0.4%.

关 键 词：Anomaly detection anomaly-based IDS Industrial Internet of Things(IIoT) IOT industrial control systems(ICSs) X-IIoTID 

分 类 号：TP391.44[自动化与计算机技术—计算机应用技术]