AdaPhish: AI-Powered Adaptive Defense and Education Resource Against Deceptive Emails
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Abstract (arXiv)
Phishing attacks remain a significant threat in the digital age, yet organizations lack effective methods to tackle phishing attacks without leaking sensitive information. Phish bowl initiatives are a vital part of cybersecurity efforts against these attacks. However, traditional phish bowls require manual anonymization and are often limited to internal use. To overcome these limitations, we introduce AdaPhish, an AI-powered phish bowl platform that automatically anonymizes and analyzes phishing emails using large language models (LLMs) and vector databases. AdaPhish achieves real-time detection and adaptation to new phishing tactics while enabling long-term tracking of phishing trends. Through automated reporting, adaptive analysis, and real-time alerts, AdaPhish presents a scalable, collaborative solution for phishing detection and cybersecurity education.
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References · 6
- 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,459
- 2024Fine-Tuned 'Small' LLMs (Still) Significantly Outperform Zero-Shot Generative AI Models in Text Classificationcited by 70
- 2024ChatSpamDetector: Leveraging Large Language Models for Effective Phishing Email Detectioncited by 25
- 2018A Deep Learning Model with Hierarchical LSTMs and Supervised Attention for Anti-Phishingcited by 4
- 2024Exploring the Efficacy of Federated-Continual Learning Nodes with Attention-Based Classifier for Robust Web Phishing Detection: An Empirical Investigationcited by 3
- 2021Federated Phish Bowl: LSTM-Based Decentralized Phishing Email Detectioncited by 2
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