An evolutionary multi-hidden Markov model for intelligent threat sensing in industrial internet of things
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An evolutionary multi‑hidden Markov model for intelligent threat sensing in industrial internet of things Mohammad Ayoub Khan1 · Khaled Ali Abuhasel2 Accepted: 16 November 2020 © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Threat problem has become more complex in the industrial environment due to the need to secure a large number of devices from attack while maintaining system reliability and real-time response to threats. In such scenario detection of threat in Industrial Internet of things (IIoT) devices becomes an important factor to avoid injection by malicious IIoT devices. The techniques based on the Hidden Markov Models (HMM) are probably the most popular in detecting threat of detection. However, HMM requires extensive training of the models and computational resources. Also, HMM has the drawback of convergence to a local optimum while using Baum– Welch algorithm for parameter estimation. In order to optimize the HMM parameters, global search techniques can be used. This work proposes Genetic algorithms (GA) for optimizing HMM parameters. The other difficulty in threat detection is the dynamic nature of the attack. Several new threats are emerging with many variants which are created from existing attacks, making threat modeling an arduous task. As a result, good features are critical to model traffic and provide an efficient way to detect known and possibly unknown attacks to detect. To achieve a better feature extraction from the network traffic, we propose a dynamic sliding window W which has a width of w . The proposed multiple-HMM performs well to detect threats. The simulation results are compared to the results obtained by the Baum–Welch algorithm based approach showing higher accuracy and convergences. Keywords Industrial IoT · HMM · Threat detection · GA · Sliding window
* Khaled Ali Abuhasel [email protected] Mohammad Ayoub Khan [email protected] 1
College of Computing and Information Technology, University of Bisha, Bisha 67714, Kingdom of Saudi Arabia
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Mechanical Engineering Department, College of Engineering, University of Bisha, Bisha 61421, Kingdom of Saudi Arabia
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M. A. Khan, K. A. Abuhasel
1 Introduction We are the part of an era in which every human being needs technology. This is evident in almost everything that our dependence on technology is growing. This trend helps to expand Internet of things (IoT) devices in different segments of the lives, such as the logistics chain, medical care and transportation, that have reached their critical level and have become a reality in our everyday lives. The (IoT) can be defined as a communication infrastructure and methodology between things. The IoT products and services can change the living style, work automation and efficiency by allowing access to the information at fingertips but at the same time introducing threat in the system [1]. For example, accessing data and information may pose serious risks to network security by introducing viruses that can devastatingly affe
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