CPU-Auth：基于DVFS侧信道的设备指纹认证技术
CPU-Auth: Device Fingerprinting for Authentication via DVFS Side-Channel
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中文总结 AI 辅助
本研究提出基于CPU物理特性的新型认证机制CPU-Auth，通过浏览器远程测量DVFS调控器行为建立硬件设备指纹，经5万余条数据轨迹评估性能，为解决现有认证缺陷提供新方案。
中文摘要 AI 辅助
缺乏有效的认证机制已导致大量安全与隐私泄露事件，包括未授权访问受保护信息、身份盗窃及欺诈。缓解此类攻击的一种方法是多因素认证（MFA），用户需提供多类信息完成认证。部分次要认证因素包括短信验证码、生物识别技术及令牌，每类均存在显著缺陷：短信安全性极差；生物识别依赖敏感个人数据访问；令牌需依赖第三方提供商（如OAuth提供商）。本研究探索CPU-Auth，一种基于计算设备CPU物理特性独特差异的新型认证机制。通过在浏览器内远程测量动态电压频率调节（DVFS）调控器的行为，可利用CPU的独特属性建立基于硬件的设备指纹，用于CPU-Auth。本研究使用距离法及深度学习方法，基于超过5万条数据轨迹评估CPU-Auth的性能。CPU-Auth是一个更大研究项目的组成部分，本报告提供的结果仅反映本团队成员对该项目的贡献。
英文摘要
Lack of effective authentication has resulted in numerous security and privacy breaches, including unauthorized access to protected information, identity theft, and fraud. One approach to mitigating such attacks is Multi-Factor Authentication (MFA), in which users must provide multiple pieces of information for authentication. Some secondary authentication factors include SMS text verification codes, biometrics, and tokens. Each contains at least one notable flaw: SMS is notoriously insecure; biometrics rely upon access to sensitive personal data; and tokens require dependence on third-party providers (e.g. OAuth providers). This work explores CPU-Auth, a novel authentication mechanism based on unique variations in the physical characteristics of the CPU of a computing device. By measuring the behavior of the Dynamic Voltage and Frequency Scaling (DVFS) governor remotely from within a browser, unique properties of the CPU can be leveraged to establish a hardware-based device fingerprint for use in CPU-Auth. The performance of CPU-Auth is evaluated on over 50,000 data traces using distance-based and deep learning methods. CPU-Auth is part of a larger research project, and the results provided in this report reflect only the contributions made to the project by members of this group.
发表机构
- University of California, Davis（加州大学戴维斯分校）
机构由 AI 辅助整理，请以论文原文为准。
