Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia.
Presidency of Ministries, Establishment of Martyrs, Baghdad, Iraq.
J Med Syst. 2019 May 22;43(7):192. doi: 10.1007/s10916-019-1264-y.
In medical systems for patient's authentication, keeping biometric data secure is a general problem. Many studies have presented various ways of protecting biometric data especially finger vein biometric data. Thus, It is needs to find better ways of securing this data by applying the three principles of information security aforementioned, and creating a robust verification system with high levels of reliability, privacy and security. Moreover, it is very difficult to replace biometric information and any leakage of biometrics information leads to earnest risks for example replay attacks using the robbed biometric data. In this paper presented criticism and analysis to all attempts as revealed in the literature review and discussion the proposes a novel verification secure framework based confidentiality, integrity and availability (CIA) standard in triplex blockchain-particle swarm optimization (PSO)-advanced encryption standard (AES) techniques for medical systems patient's authentication. Three stages are performed on discussion. Firstly, proposes a new hybrid model pattern in order to increase the randomization based on radio frequency identification (RFID) and finger vein biometrics. To achieve this, proposed a new merge algorithm to combine the RFID features and finger vein features in one hybrid and random pattern. Secondly, how the propose verification secure framework are followed the CIA standard for telemedicine authentication by combination of AES encryption technique, blockchain and PSO in steganography technique based on proposed pattern model. Finally, discussed the validation and evaluation of the proposed verification secure framework.
在用于患者认证的医疗系统中，确保生物识别数据的安全是一个普遍存在的问题。许多研究已经提出了各种保护生物识别数据（尤其是指静脉生物识别数据）的方法。因此，需要通过应用上述信息安全的三个原则并创建一个具有高可靠性、隐私性和安全性的强大验证系统，找到保护这些数据的更好方法。此外，生物识别信息很难被替换，任何生物识别信息的泄露都会导致严重的风险，例如使用被盗的生物识别数据进行重播攻击。本文对文献综述中揭示的所有尝试进行了批评和分析，并讨论了一种基于三重区块链-粒子群优化（PSO）-高级加密标准（AES）技术的新型保密、完整和可用（CIA）标准的用于医疗系统患者认证的验证安全框架。讨论分三个阶段进行。首先，提出了一种新的混合模型模式，以增加基于射频识别（RFID）和指静脉生物识别的随机性。为此，提出了一种新的合并算法，将 RFID 特征和指静脉特征合并为一个混合随机模式。其次，如何通过将 AES 加密技术、区块链和 PSO 结合在基于所提出模式模型的隐写术中，遵循 CIA 标准进行远程医疗认证。最后，讨论了所提出的验证安全框架的验证和评估。
