论密码协议中使用患者生理信号的难点

Eduard Marin, Enrique Argones-Rúa, Dave Singelée, B. Preneel
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引用次数: 6

摘要

随着可穿戴传感器和植入式医疗设备的功能不断增强,出现了诊断、控制和治疗多种慢性疾病的新机会。不幸的是,这些进步也带来了新的攻击媒介,使安全性成为进一步采用这些设备的基本要求。研究人员已经开发出针对其独特需求和限制的安全解决方案。然而,如何安全有效地建立和管理密钥是一个尚未解决的基本问题。利用患者的生理信号进行键的建立是最有前途的方法之一。本文旨在识别基于生理信号的加密协议中的常见缺陷。这些解决方案非常脆弱,因为在不同阶段可能会引入错误,包括生理信号的选择、协议的设计或实施。我们首先回顾了以前成功地远程测量各种生理信号的工作。随后,我们对安全社区广泛接受的两种加密解决方案进行了彻底的安全分析,即H2H协议(Rostami等人- CCS 2013)和Biosec协议(Cherukuri等人- ICISIP 2006)。我们的评估显示,这些协议具有严重的设计和实现安全弱点。基于我们的发现,我们随后描述了如何使用模糊提取器来设计基于患者生理信号的安全高效的加密解决方案。最后,讨论了今后工作的研究方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On the Difficulty of Using Patient's Physiological Signals in Cryptographic Protocols
With the increasing capabilities of wearable sensors and implantable medical devices, new opportunities arise to diagnose, control and treat several chronic conditions. Unfortunately, these advancements also open new attack vectors, making security an essential requirement for the further adoption of these devices. Researchers have already developed security solutions tailored to their unique requirements and constraints. However, a fundamental yet unsolved problem is how to securely and efficiently establish and manage cryptographic keys. One of the most promising approaches is the use of patient's physiological signals for key establishment. This paper aims at identifying common pitfalls in physiological-signal-based cryptographic protocols. These solutions are very fragile because errors can be introduced at different stages, including the choice of the physiological signal, the design of the protocol or its implementation. We start by reviewing previous work that has succeeded in measuring various physiological signals remotely. Subsequently, we conduct a thorough security analysis of two cryptographic solutions well-accepted by the security community, namely the H2H protocol (Rostami et al. - CCS 2013) and the Biosec protocol (Cherukuri et al. - ICISIP 2006). Our evaluation reveals that these protocols have serious design and implementation security weaknesses. Driven by our findings, we then describe how to use fuzzy extractors for designing secure and efficient cryptographic solutions based on the patients' physiological signals. Finally, we discuss research directions for future work.
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