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Machine Learning Based Intrusion Detection Systems for IoT Applications. (arXiv:2302.12452v1 [cs.CR])
cs.CR updates on arXiv.org arxiv.org
Internet of Things (IoT) and its applications are the most popular research
areas at present. The characteristics of IoT on one side make it easily
applicable to real-life applications, whereas on the other side expose it to
cyber threats. Denial of Service (DoS) is one of the most catastrophic attacks
against IoT. In this paper, we investigate the prospects of using machine
learning classification algorithms for securing IoT against DoS attacks. A
comprehensive study is carried on the classifiers which …
algorithms applications attacks classification cyber cyber threats denial of service detection dos internet internet of things intrusion intrusion detection iot iot applications life machine machine learning popular research securing iot service systems things threats