Email Phishing Detection Using Artificial Intelligence and Machine Learning
Author(s): 1. Dr. Dnyanda Hire , 2.Shivam Suryavanshi , 3.Tejas Dhokane, 4.Pratik Deshmukh.
Authors Affiliations:
1.Professor, 2.,3,4Student,
1,2,3,4.Electronics and Telecommunication Engineering, Dr. D Y Patil Institute of Engineering Management and Research, Pune, India
DOIs:10.2015/IJIRMF/202604006 | Paper ID: IJIRMF202604006Phishing attacks have now been identified as one of the biggest security threats in the recent past. Phishing attacks may involve the use of emails that may resemble emails from trusted organizations with the aim of extracting information from the victims, such as login information, financial information, etc. The traditional approach to phishing attacks that relies on the filtering and blacklisting approach has now become obsolete due to the constant changes in the approaches and formats of the emails by the attackers to evade the detection systems. Recently, Artificial Intelligence and Machine Learning approaches have been identified as effective in the automatic detection of phishing attacks. These approaches have the ability to analyze different characteristics of the emails that may contain malicious content, such as the content of the emails, sender details, links, etc. The advantages and disadvantages of different research works on the effectiveness of Machine Learning and Deep Learning approaches in the detection of phishing attacks and malicious emails have been discussed in this study.
Dr. Dnyanda Hire , Shivam Suryavanshi , Tejas Dhokane, Pratik Deshmukh. (2026); Email Phishing Detection Using Artificial Intelligence and Machine Learning, International Journal for Innovative Research in Multidisciplinary Field, ISSN(O): 2455-0620, Vol-12, Issue-4, Available on – https://www.ijirmf.com/
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