在完全加密的域中进行身份匹配的时间指纹
Shahar Somin1,2, Keeley Erhardt3, Tom Cohen3
1MIT, Cambridge, MA, USA. shaharso@mit.edu.
Nature communications
|October 28, 2025
概括
这项研究引入了一个新的框架,用于在线平台上检测协调的非真实行为. 它有效地与使用活动模式的假名配置文件进行匹配,增强数字安全性.
科学领域:
- 计算机科学 计算机科学
- 网络科学 网络科学
- 网络安全 网络安全
背景情况:
- 协调不真实的行为 (CIB) 对社会稳定,市场和安全构成重大威胁.
- 生成型人工智能通过使复杂的内容创建和放大恶意行为者的影响来加剧这些威胁.
- 由于假名配置文件的跨域活动和限制隐私限制内容分析,检测CIB具有挑战性.
研究的目的:
- 提出一个强大的和可扩展的跨域身份匹配框架,用于检测协调的非真实行为.
- 开发一种独立于内容或交互数据的方法,专注于行为动态.
- 为打击数字威胁提供理论和方法的贡献.
主要方法:
- 开发了一个基于 bursty 动态的跨域身份匹配框架.
- 根据最先进的时间和结构方法评估了框架的表现.
- 评估了在多个在线市场上对不完整数据的可扩展性和弹性.
主要成果:
- 拟议的框架在检测协调的虚假行为方面优于现有的方法.
- 它表现出对不完整数据的弹性,在52周后识别了35%的个人资料.
- 在500个市场的身份匹配时,实现了0.78的曲线下面面积 (AUC),每日交易员超过25万.
结论:
- 基于bursty动态的框架为跨域身份匹配提供了一个可扩展和有效的解决方案.
- 这种方法提高了在复杂的数字生态系统中打击协调不真实的行为的能力.
- 在"网络的网络"视角中对身份匹配的框架揭示了协调行为的传播模式.
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