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ISSN Number:
2582-8568


Journal DOI No:
03.2021-11278686

Title:
Machine Learning to Detect Email Attacks: A Review

Authors:
Annasaheb M. Chougule , Dr. Kavita S. Oza , Rohit B. Diwane

Cite this Article:
Annasaheb M. Chougule , Dr. Kavita S. Oza , Rohit B. Diwane ,
Machine Learning to Detect Email Attacks: A Review,
International Research Journal of Humanities and Interdisciplinary Studies (www.irjhis.com), ISSN : 2582-8568, Volume: 4, Issue: 6, Year: June 2023, Page No : 151-161,
Available at : http://irjhis.com/paper/IRJHIS2306021.pdf

Abstract:

Email attacks have become a prevalent problem in the digital world. With the increasing amount of sensitive information being sent through emails, it has become essential to develop efficient techniques to detect email attacks. Machine learning, which is a subset of artificial intelligence, has proven to be an effective tool for detecting email attacks. In this article, we will discuss the design and development of machine learning models to detect email attacks. In this research paper we are reviewed recent research papers with key points and research gaps in tabular format. The number of published studies that were studied carefully and critically and added to the importance of email attacks detection and prevention.



Keywords:

email attacks, machine learning, Artificial Intelligence, natural language processing, phishing, spam, smishing.



Publication Details:
Published Paper ID: IRJHIS2306021
Registration ID: 21100
Published In: Volume: 4, Issue: 6, Year: June 2023
Page No: 151-161
ISSN Number: 2582-8568

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ISSN Number

ISSN 2582-8568

Impact Factor

5.71 (2021)

DOI Member


03.2021-11278686