Authors: Takashi Koide, Naoki Fukushi, Hiroki Nakano, Daiki Chiba

Published on: February 28, 2024

Impact Score: 7.4

Arxiv code: Arxiv:2402.18093

Summary

• What is new: Introduction of ChatSpamDetector, a system utilizing large language models (LLMs) for the high-accuracy detection of phishing emails, with detailed reasoning for its decisions.
• Why this is important: The ongoing issue of phishing sites and emails, and the limitations of current spam filters and security protocols in correctly identifying and explaining why emails are flagged.
• What the research proposes: ChatSpamDetector system that leverages GPT-4 to assess and explain whether an email is phishing, enhancing user understanding and decision-making regarding suspicious emails.
• Results: Achieved a 99.70% accuracy in detecting phishing emails, outperforming several LLMs and baseline systems, with advanced contextual interpretation pinpointing various phishing tactics.

Technical Details

Technological frameworks used: ChatSpamDetector

Models used: GPT-4

Data used: Comprehensive phishing email dataset

Potential Impact

Cybersecurity providers, email service providers, companies reliant on email communications could benefit from implementing such a system to protect against phishing attacks.

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