International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 7, Issue 3 (May-June 2025) Submit your research before last 3 days of June to publish your research paper in the issue of May-June.
Submit Research Paper Join as a Reviewer

Plagiarism is checked by the leading plagiarism checker TurnItIn

Call for Paper

Volume 7 Issue 3
May-June 2025

Submit your research paper

Indexing Partners
Academia Advanced Sciences Index Bielefeld Academic Search Engine CiteSeer DRJI Google Scholar Independent Search Engine & Directory Network ISI (International Scientific Indexing) Issuu Mendeley Research Networks
RefSeek ResearcherId - Thomson Reuters ResearchGate Scirus Scribd Semantic Scholar UTeM - Universiti Teknikal Malaysia Melaka Wiki for Call for Papers WorldCat Zenodo

Phishing Email Detection using AI

Author(s) Mr. Armaan Shoaib Shaik, Mr. Sathish Sanke, Ms. Shirisha Kampati, Mr. Satya Shekhar Varma
Country India
Abstract Phishing emails continue to pose a significant threat, causing financial
losses and security breaches. This solution addresses limitations in
existing applications, such as reliance on proprietary datasets and lack of
real-world application, by proposing a high-performance machine learning
model for email classification. Phishing email detection using Artificial
Intelligence (AI) is an innovative approach against the ever-growing threat
of email-based cyberattacks. This project uses advanced machine learning
algorithms through AI to classify emails into categories such as phishing
and safe.
Real-time analysis capabilities allow it to detect threats in real time;
the continuous learning mechanism by the system allows it to adapt to
new phishing tactics and evolving cybersecurity threats. This is a
significant improvement from conventional methods, with a detection rate
of over 95% while maintaining very low false-positive rates. The solution
includes visualization tools for threat analysis and reporting, which
enables security teams to better understand attack patterns and trends.
This is a highly accurate, scalable and adaptable AI driven solution
with application for use in enterprise email security systems.
Keywords Phishing Detection, Artificial Intelligence, Machine Learning, Email Security, Application Programming Interface (API)
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 7, Issue 3, May-June 2025
Published On 2025-05-09
View / Download PDF File

Share this



E-ISSN 2582-2160
CrossRef

CrossRef DOI is assigned to each research paper published in our journal.

IJFMR DOI prefix is
10.36948/ijfmr

Downloads
Research Paper Format Copyright Permission Form and Undertaking Form Cover Page Vol 7 Isu 2Cover Page Vol 7 Isu 1Cover Page Vol 6 Isu 6

All research papers published on this website are licensed under Creative Commons Attribution-ShareAlike 4.0 International License, and all rights belong to their respective authors/researchers.

CC-BY-SA Open Access

About IJFMR
Fees & Payment
Current Issue
Publication Archive 		Submit Research Paper
Track Submission Status
Publication Guidelines
Publication Ethics
Peer Review & Plagiarism 		Join as a Reviewer
Editors & Reviewers
Reviewer Referral Program
Get Reviewer Membership Certi. 		Website/Journal Policies
Usage Policy
Content Policies
Privacy Policy
Contact Us +91-9687-828-838 editor@ijfmr.com