LLM-Based Framework for Email Classification and Phishing Detection
Phishing and spam attacks continue to pose significant security risks due to their evolving nature, with traditional email classification methods often unable to effectively address these challenges. This paper proposes a framework that uses Large Language Models (LLMs) for enhanced email categorization and phishing detection. Through an inbox plugin, a user reports an email, which is then stored in a database, cleaned, and thoroughly analyzed using a series of specific prompts determining a classification of "normal", "unwanted", or "malicious" email.
Authors
- José Cecílio (ORCID: https://orcid.org/0000-0002-5351-5580)
- Dulce Domingos (ORCID: https://orcid.org/0000-0002-5829-2742)
- Mónica Rosa
- Nuno Costa
- Ruben Salgueiro
Institutions
- University of Lisbon (PT)
- Universidade Europeia (PT)
Publication Details
- Journal
- ACM SIGAda Ada Letters
- Published
- 2025-06-01
- DOI
- https://doi.org/10.1145/3784987.3784993
- Primary Topic
- Spam and Phishing Detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00