INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
ABSTRACT
There are many IoT-based social media platforms and applications. Spam problems are increasingly expanding as a result of IoT growth. The researchers offered a range of spam detection tools to recognise and filter spam and spammers. Even with all of the anti-spam tools and techniques out there, the spam rate is still quite high. The most dangerous kinds of spam are emails that contain links to websites that can damage the victim's data. Spam emails can slow down a server's response time by consuming memory or storage space on the server.Among all the techniques developed for locating and blocking spam, email filtering is one of the most significant and well-known. Machine learning and deep learning techniques have been used for this, including Naive Bayes, decision trees, SVM, and random forest. This paper examines the machine learning techniques used for spam filtering in email and IoT platforms by grouping them into useful categories.
A bulk mailing can be used to send hundreds of thousands of spam letters in just a few minutes. Most typically, spam emanates via zombie networks, which are made up of numerous computers that have been infected with malicious software.
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Cite Article:
"Email Fraud Detection System", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 6, page no.a613-a619, June-2023, Available :http://www.ijnrd.org/papers/IJNRD2306072.pdf
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ISSN:
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
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