GView用视觉与AI增强分析，提升二进制取证效率
GView: A Survey of Binary Forensics via Visual, Semantic, and AI-Enhanced Analysis
- 融合视觉分析与大语言模型动态推理
- 通过逻辑谓词和规则实现行为与文档的智能推断
- 架构可扩展，适合产业界与学术界协同应用
网络攻击手段日益复杂多样，带来海量且高复杂度的数字证据。为应对挑战，本文介绍GView——一个开源的二进制取证分析框架，具备可视化与AI增强推理能力。最初聚焦于实际网络安全产业需求，现已发展为集成大语言模型（LLMs）的动态推理系统，显著简化取证流程。本综述涵盖已发表及在审论文成果，重点展示其通过谓词与推理规则对分析文档及用户操作进行逻辑推断的创新机制。框架具有高度可扩展性，有望成为连接产业实践与学术研究的重要桥梁。
原文摘要 · Abstract (English)
Cybersecurity threats continue to become more sophisticated and diverse in their artifacts, boosting both their volume and complexity. To overcome those challenges, we present GView, an open-source forensic analysis framework with visual and AI-enhanced reasoning. It started with focus on the practical cybersecurity industry. It has evolved significantly, incorporating large language models (LLMs) to dynamically enhance reasoning and ease the forensic workflows. This paper surveys both the current state of GView with its published papers alongside those that are in the publishing process. It also includes its innovative use of logical inference through predicates and inference rules for both the analyzed documents and the user's actions for better suggestions. We highlight the extensible architecture, showcasing its potential as a bridge between the practical forensics worlds with the academic research.
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