{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,22]],"date-time":"2026-07-22T16:19:18Z","timestamp":1784737158599,"version":"3.55.0"},"reference-count":88,"publisher":"Wiley","license":[{"start":{"date-parts":[[2022,2,3]],"date-time":"2022-02-03T00:00:00Z","timestamp":1643846400000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100006261","name":"Taif University","doi-asserted-by":"publisher","award":["TURSP-2020\/314"],"award-info":[{"award-number":["TURSP-2020\/314"]}],"id":[{"id":"10.13039\/501100006261","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Security and Communication Networks"],"published-print":{"date-parts":[[2022,2,3]]},"abstract":"<jats:p>Nowaday, emails are used in almost every field, from business to education. Emails have two subcategories, i.e., ham and spam. Email spam, also called junk emails or unwanted emails, is a type of email that can be used to harm any user by wasting his\/her time, computing resources, and stealing valuable information. The ratio of spam emails is increasing rapidly day by day. Spam detection and filtration are significant and enormous problems for email and IoT service providers nowadays. Among all the techniques developed for detecting and preventing spam, filtering email is one of the most essential and prominent approaches. Several machine learning and deep learning techniques have been used for this purpose, i.e., Na\u00efve Bayes, decision trees, neural networks, and random forest. This paper surveys the machine learning techniques used for spam filtering techniques used in email and IoT platforms by classifying them into suitable categories. A comprehensive comparison of these techniques is also made based on accuracy, precision, recall, etc. In the end, comprehensive insights and future research directions are also discussed.<\/jats:p>","DOI":"10.1155\/2022\/1862888","type":"journal-article","created":{"date-parts":[[2022,2,3]],"date-time":"2022-02-03T18:50:16Z","timestamp":1643914216000},"page":"1-19","source":"Crossref","is-referenced-by-count":134,"title":["Machine Learning Techniques for Spam Detection in Email and IoT Platforms: Analysis and Research Challenges"],"prefix":"10.1155","volume":"2022","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1850-5846","authenticated-orcid":true,"given":"Naeem","family":"Ahmed","sequence":"first","affiliation":[{"name":"Department of Computer Science, University of Engineering and Technology, Taxila, Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3143-689X","authenticated-orcid":true,"given":"Rashid","family":"Amin","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Engineering and Technology, Taxila, Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hamza","family":"Aldabbas","sequence":"additional","affiliation":[{"name":"Prince Abdullah Bin Ghazi Faculty of Information and Communication Technology, Al-Balqa Applied University, Al-Salt, Jordan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Deepika","family":"Koundal","sequence":"additional","affiliation":[{"name":"Department of Systemics, School of Computer Science, University of Petroleum & Energy Studies, Dehradun, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bader","family":"Alouffi","sequence":"additional","affiliation":[{"name":"Department of Computer Science, College of Computers and Information Technology, Taif University, P.O. 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