Phishsense-1B: A Technical Perspective on an AI-Powered Phishing Detection Model

• URL: http://arxiv.org/abs/2503.10944v1
• Date: Thu, 13 Mar 2025 23:03:09 GMT
• Title: Phishsense-1B: A Technical Perspective on an AI-Powered Phishing Detection Model
• Authors: SE Blake,
• Abstract summary: Phishing is a persistent cybersecurity threat in today's digital landscape.<n>This paper introduces Phishsense-1B, a refined version of the Llama-Guard-3-1B model, specifically tailored for phishing detection and reasoning.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Phishing is a persistent cybersecurity threat in today's digital landscape. This paper introduces Phishsense-1B, a refined version of the Llama-Guard-3-1B model, specifically tailored for phishing detection and reasoning. This adaptation utilizes Low-Rank Adaptation (LoRA) and the GuardReasoner finetuning methodology. We outline our LoRA-based fine-tuning process, describe the balanced dataset comprising phishing and benign emails, and highlight significant performance improvements over the original model. Our findings indicate that Phishsense-1B achieves an impressive 97.5% accuracy on a custom dataset and maintains strong performance with 70% accuracy on a challenging real-world dataset. This performance notably surpasses both unadapted models and BERT-based detectors. Additionally, we examine current state-of-the-art detection methods, compare prompt-engineering with fine-tuning strategies, and explore potential deployment scenarios.

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