用AI自动处理钓鱼邮件，实现实时防御与教育。
AdaPhish: AI-Powered Adaptive Defense and Education Resource Against Deceptive Emails
- 用大模型和向量库自动匿名化并分析钓鱼邮件
- 支持实时检测新攻击手法并长期追踪趋势
- 适合需要协作防御与安全教育的组织
钓鱼攻击仍是数字时代的主要威胁，但组织缺乏不泄露敏感信息的有效应对方法。钓鱼沙盘（Phish bowl）是网络安全的重要举措，但传统方式需人工匿名化，且多限于内部使用。为克服这些局限，我们提出AdaPhish——一个基于大语言模型（LLMs）和向量数据库的AI驱动钓鱼沙盘平台，可自动匿名化并分析钓鱼邮件。该平台实现对新型钓鱼手段的实时检测与自适应响应，并支持长期钓鱼趋势追踪。通过自动化报告、自适应分析和实时警报，AdaPhish提供了一种可扩展、可协作的钓鱼检测与网络安全教育解决方案。
原文摘要 · Abstract (English)
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.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。