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All Journal JOIV : International Journal on Informatics Visualization
Nor Asiakin Hasbullah
Computer Science Department, Universiti Pertahanan Nasional Malaysia
Computer Science & IT

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IoT Attack Detection using Machine Learning and Deep Learning in Smart Home S Azli Sham, Sharifah Nabila; Ishak, Khairul Khalil; Mat Razali, Noor Afiza; Mohd Noor, Normaizeerah; Hasbullah, Nor Asiakin
JOIV : International Journal on Informatics Visualization Vol 8, No 1 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.1.2174

Abstract

The Internet of Things (IoT) has revolutionized the traditional Internet, pushing past its former boundaries by implementing smart linked gadgets. The IoT is steadily becoming a staple of everyday life, having been implemented into various diverse applications, such as cities, smart homes, and transportation.  However, despite the technological advancements that the IoT brings, various new security risks have also been introduced due to the development of new types of attacks. This prevents current intelligent IoT applications from adaptively learning from other intelligent IoT applications, which leaves them in a volatile state. In this paper, we conducted a structured literature review (SLR) on Smart Home's IoT attack detection using machine learning and deep learning. Four journal databases were used to perform this review: IEEE, Science Direct, Association for Computing Machinery (ACM), and SpringerLink. Sixty articles were selected and studied, where we noted the various patterns and techniques present in the framework of the selected research. We also took note of the different machine learning and deep learning methods, the types of attacks, and the Network layers present in Smart Home. By conducting an SLR, we analyzed the numerous techniques of IoT attack detection for smart homes proposed by various theoretical studies. We enhanced the studied literature by proposing a new solution for better IoT attack detection in smart homes.
Co-Authors Ishak, Khairul Khalil Mat Razali, Noor Afiza Mohd Noor, Normaizeerah S Azli Sham, Sharifah Nabila