Healthcare Security: Post-Quantum Continuous Authentication With Behavioral Biometrics Using Vector Similarity Search

IF 8 1区 计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS IEEE Transactions on Information Forensics and Security Pub Date : 2025-01-17 DOI:10.1109/TIFS.2025.3531197
Basudeb Bera;Sutanu Nandi;Ashok Kumar Das;Biplab Sikdar
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Abstract

With the increasing digitization of medical records and the interconnected nature of healthcare networks, robust security measures are vital to mitigate the risk of data breaches, cyberattacks, and unauthorized access. Existing healthcare security models, like one-time authentication (OTA), rely on complex mathematical problems such as the integer factorization problem (IFP) and discrete logarithm problem (DLP). However, advancements in quantum computing, notably Shor’s algorithm, pose a threat to the security of these systems. Once the attacker bypasses OTA, they gain permanent access and can reveal sensitive healthcare user information. Given the numerous vulnerabilities exposed in OTA systems, there is a rising demand and trend toward implementing continuous authentication systems. Current cutting-edge privacy technologies either are not feasible or entail high costs for continuous authentication systems, which necessitate periodic real-time verification. As a result, we proposed a cutting-edge novel approach to healthcare security through post-quantum continuous authentication without breaking the continuity of a session, leveraging behavioral biometrics (BB) and vector similarity search (VSS). By integrating BB, which analyzes individual behavioral patterns, with VSS, our robust lightweight quantum-secure technique ensures a heightened level of security. The proposed framework offers seamless and continuous authentication, adapting in real-time to users’ behavioral patterns. The proof of concept for VSS demonstrates the efficiency of the proposed scheme in real-time healthcare applications. Through extensive testing, analysis, and performance analysis under unknown attacks, this study demonstrates the efficacy and resilience of our approach, promising a new frontier in healthcare security. A real-time testbed experiment, along with the implementation and design of FastAPI, demonstrates the novelty of the proposed scheme.
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医疗安全:使用向量相似性搜索的行为生物识别技术的后量子连续身份验证
随着医疗记录的日益数字化和医疗网络的互联性,强大的安全措施对于降低数据泄露、网络攻击和未经授权访问的风险至关重要。现有的医疗保健安全模型,如一次性身份验证(OTA),依赖于复杂的数学问题,如整数分解问题(IFP)和离散对数问题(DLP)。然而,量子计算的进步,特别是肖尔算法,对这些系统的安全构成了威胁。一旦攻击者绕过OTA,他们就获得了永久访问权限,并可能泄露敏感的医疗保健用户信息。考虑到OTA系统中暴露的众多漏洞,实现连续身份验证系统的需求和趋势不断增长。当前的尖端隐私技术要么不可行,要么对需要定期实时验证的连续身份验证系统来说成本很高。因此,我们提出了一种利用行为生物识别(BB)和向量相似性搜索(VSS),在不破坏会话连续性的情况下,通过后量子连续身份验证来实现医疗安全的前沿新方法。通过将分析个人行为模式的BB与VSS相结合,我们强大的轻量级量子安全技术确保了更高的安全性。所提出的框架提供无缝和连续的身份验证,实时适应用户的行为模式。VSS的概念验证证明了所提出的方案在实时医疗保健应用中的有效性。通过在未知攻击下进行广泛的测试、分析和性能分析,本研究证明了我们的方法的有效性和弹性,有望在医疗保健安全领域开辟新的前沿。实时试验台实验,以及FastAPI的实现和设计,证明了该方案的新颖性。
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来源期刊
IEEE Transactions on Information Forensics and Security
IEEE Transactions on Information Forensics and Security 工程技术-工程:电子与电气
CiteScore
14.40
自引率
7.40%
发文量
234
审稿时长
6.5 months
期刊介绍: The IEEE Transactions on Information Forensics and Security covers the sciences, technologies, and applications relating to information forensics, information security, biometrics, surveillance and systems applications that incorporate these features
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