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A Review on Machine Learning-based Malware Detection Techniques for Internet of Things (IoT) Environments

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Abstract

Internet of Things (IoT) is the recent digital trend that connects the physical and virtual world. The strong bonding between the people, objects, machines and the web are assisting to develop new business models and also ensuring a better communication framework. On the other side, IoT devices are the main targets for cybercriminals that take vulnerable action over the authentication model, outdated data services and the malware. Henceforth, the security metrics of IoT devices is explored by several researchers while focusing on IoT malware. Many studies on the security issues for IoT systems are explored. Specifically, the employment of Machine learning techniques used for detecting the IoT malwares is studied. In this paper, a detailed survey on detecting the IoT malware using ML techniques are presented. Initially, the fundamentals of the malware analysis and the process and tools used to identify the malwares are discussed. The main intention of this survey is to support the security analysts who are interested to understand and innovate new trends in ML for IoT devices. This study is categorized into two groups, namely, machine learning techniques and neural networks. Both the groups are reviewed from the aspects of preprocessing and feature extraction process of the suggested ML techniques. The study ends the research issues in this field from the aspects of evaluating the performance of methods, as dataset collection, parameter optimization, neural network structure, throughput and scalability.

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Authors and Affiliations

  1. Department of Information Technology, CVR College of Engineering, Mangalpally, Vastunagar, 501510, Telangana, India

    S. Sasikala & Sengathir Janakiraman

  2. School of Computing, Edinburgh Napier University, EH10 5DT, Edinburgh, United Kingdom

    S. Sasikala

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  1. S. Sasikala
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  2. Sengathir Janakiraman
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Sasikala has written the abstract, introduction, literature review and, Sengathir identified the research gaps with complete review of the manuscript.

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Correspondence to Sengathir Janakiraman.

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Sasikala, S., Janakiraman, S. A Review on Machine Learning-based Malware Detection Techniques for Internet of Things (IoT) Environments. Wireless Pers Commun 132, 1961–1974 (2023). https://doi.org/10.1007/s11277-023-10693-w

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