DETECTION OF PHISHING E-MAIL THROUGH THE USE OF MACHINE LEARNING

Registration ID: IJNRD_226738

Published ID: IJNRD2408244

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lakshmi vijetha sanku , Marna.Yamini Lahari

Phishing email, Random Forest Classifier, Logistic Regression

: Email phishing is a type of cyber-attack that attempts to steal sensitive information by disguising as legitimate sources. Machine learning has the potential to detect email phishing attacks, and this paper presents an overview of the proposed machine learning-based approach for detection. The proposed approach involves feature extraction from emails, including message content, header information, and is used to train and test machine learning models. It checks several approaches for detecting the phishing mails. It uses supervised learning algorithms like logistic regressions, decision trees, random forests to classify incoming emails as either legitimate or phishing attempts. We calculate the accuracy for all the methods implemented to classify the mails. The results show that the proposed approach achieves high accuracy and outperforms existing approaches, and can be used by organizations and individuals to improve their email security.

Published Paper   E-Certificate

lakshmi vijetha sanku & Marna.Yamini Lahari (August-2024). DETECTION OF PHISHING E-MAIL THROUGH THE USE OF MACHINE LEARNING. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(8), c410-c419. https://ijnrd.org/papers/IJNRD2408244.pdf

Volume 9 Issue 8, August-2024

Pages : c410-c419

Paper Reg. ID: IJNRD_226738

Published Paper Id: IJNRD2408244

Downloads: 000121981

Research Area: Computer Science & Technology 

Country: eluru, Andhra Pradesh, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2408244.pdf

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Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

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