Sridevi, V and Saravanakumar, SM (2025) Social engineering and spam detection of AI-driven Phishing emails. Social engineering and spam detection of AI-driven Phishing emails, 12 (3): 183747. pp. 2725-2731. ISSN 2349-6002

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Abstract

Natural language processing has been
transformed by the sophisticated design of advanced
Language Modelswhich produces text that accurately
appears like authentic communication including
phishing emails. Phishing emails created by AI are
becoming more common these days. This investigation
aims to address this problem by examining AI driven
emails and address how well Email services filter these
harmful messages. The results showed that that many
email services allowed more AI-driven phishing emails to
circumvent their filters. The Generative AI social
engineering conceptual model was incorporated to
explore the complexity of Ai-driven social engineering
attacks. In order to address these issues, logistic
regression and XGBoost machine learning model were
used to filter phishing emails based on factors the
number of imperative verbs andpersonal pronouns. The
Kaggle AI-generated phishing email dataset was used in
this study.

Item Type: Article
Uncontrolled Keywords: AI-driven phishing email, Textual and style analysis, Advanced Language Models (ALMs), Machine learning, cyber-attack
Divisions: PSG College of Arts and Science > Department of Computer Science
Depositing User: Mr Team Mosys
Date Deposited: 06 Oct 2025 05:44
Last Modified: 06 Oct 2025 05:44
URI: https://ir.psgcas.ac.in/id/eprint/2453

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