Abstract
The Internet of Things (IoT) has inexorably awakened advanced humans’ existence. Aside from the advantages that this innovative technology provides to the IoT device users, there are also cyber security concerns. Traditional cyber security approaches would not work on low-power IoT devices. As a result, numerous threat detection approaches and methods that are considerate the constraints of the Internet of Things have recently been created. To detect abnormalities in network traffic time series, this research offers a threat detection strategy that combines statistical and machine learning approaches. Furthermore, this novel architecture provides a light solution for cyber security because the logic of computing is a component of the edge layer. The technique performed nicely in spans of recall, precision, accuracy, and F-measure, according to the findings of the test bed testing.
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Jha, C.K., Biswas, S.S., Nafis, M.T. (2023). A Comprehensive System for Smart Homes with a Minimalist Information Security Framework. In: Kaiser, M.S., Xie, J., Rathore, V.S. (eds) Information and Communication Technology for Competitive Strategies (ICTCS 2021). Lecture Notes in Networks and Systems, vol 401. Springer, Singapore. https://doi.org/10.1007/978-981-19-0098-3_39
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DOI: https://doi.org/10.1007/978-981-19-0098-3_39
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