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However, the inherent vulnerabilities of the IoT have sparked concerns for wide adoption and applications. Unlike traditional information technology (I.T.) systems, the IoT environment is challenging to secure due to resource constraints, heterogeneity, and distributed nature of the smart devices. This makes it impossible to apply host-based prevention mechanisms such as anti-malware and anti-virus. These challenges and the nature of IoT applications call for a monitoring system such as anomaly detection both at device and network levels beyond the organisational boundary. This suggests an anomaly detection system is strongly positioned to secure IoT devices better than any other security mechanism. In this paper, we aim to provide an in-depth review of existing works in developing anomaly detection solutions using machine learning for protecting an IoT system. We also indicate that blockchain-based anomaly detection systems can collaboratively learn effective machine learning models to detect anomalies.<\/jats:p>","DOI":"10.3390\/s21248320","type":"journal-article","created":{"date-parts":[[2021,12,14]],"date-time":"2021-12-14T01:22:05Z","timestamp":1639444925000},"page":"8320","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":114,"title":["A Comprehensive Study of Anomaly Detection Schemes in IoT Networks Using Machine Learning Algorithms"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7147-2783","authenticated-orcid":false,"given":"Abebe","family":"Diro","sequence":"first","affiliation":[{"name":"College of Business and Law, RMIT University, Melbourne 3001, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5396-8897","authenticated-orcid":false,"given":"Naveen","family":"Chilamkurti","sequence":"additional","affiliation":[{"name":"Department of Computer Science and I.T., La Trobe University, Melbourne 3086, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5834-3709","authenticated-orcid":false,"given":"Van-Doan","family":"Nguyen","sequence":"additional","affiliation":[{"name":"Department of Computer Science and I.T., La Trobe University, Melbourne 3086, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Will","family":"Heyne","sequence":"additional","affiliation":[{"name":"BAE Systems Australia, Adelaide 5000, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,12,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Alsoufi, M.A., Razak, S., Siraj, M.M., Nafea, I., Ghaleb, F.A., Saeed, F., and Nasser, M. 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