Privacy protection for telecare medicine information systems using a chaotic map-based three-factor authenticated key agreement scheme

Telecare Medicine Information Systems (TMIS) provides flexible and convenient e-health care. However the medical records transmitted in TMIS are exposed to unsecured public networks, so TMIS are more vulnerable to various types of security threats and attacks. To provide privacy protection for TMIS, a secure and efficient authenticated key agreement scheme is urgently needed to protect the sensitive medical data. Recently, Mishra et al. proposed a biometrics-based authenticated key agreement scheme for TMIS by using hash function and nonce, they claimed that their scheme could eliminate the security weaknesses of Yan et al.’s scheme and provide dynamic identity protection and user anonymity. In this paper, however, we demonstrate that Mishra et al.’s scheme suffers from replay attacks, man-in-the-middle attacks and fails to provide perfect forward secrecy. To overcome the weaknesses of Mishra et al.’s scheme, we then propose a three-factor authenticated key agreement scheme to enable the patient enjoy the remote healthcare services via TMIS with privacy protection. The chaotic map-based cryptography is employed in the proposed scheme to achieve a delicate balance of security and performance. Security analysis demonstrates that the proposed scheme resists various attacks and provides several attractive security properties. Performance evaluation shows that the proposed scheme increases efficiency in comparison with other related schemes

Privacy protection for e-health systems by means of dynamic authentication and three-factor key agreement

During the past decade, the electronic healthcare (e-health) system has been evolved into a more patient-oriented service with smaller and smarter wireless devices. However, these convenient smart devices have limited computing capacity and memory size, which makes it harder to protect the user’s massive private data in the e-health system. Although some works have established a secure session key between the user and the medical server, the weaknesses still exist in preserving the anonymity with low energy consumption. Moreover, the misuse of biometric information in key agreement process may lead to privacy disclosure, which is irreparable. In this study, we design a dynamic privacy protection mechanism offering the biometric authentication at the server side whereas the exact value of the biometric template remains unknown to the server. And the user anonymity can be fully preserved during the authentication and key negotiation process because the messages transmitted with the proposed scheme are untraceable. Furthermore, the proposed scheme is proved to be semantic secure under the Real-or-Random Model. The performance analysis shows that the proposed scheme suits the e-health environment at the aspect of security and resource occupation

INFORMATION SECURITY: A STUDY ON BIOMETRIC SECURITY SOLUTIONS FOR TELECARE MEDICAL INFORMATION SYSTEMS

This exploratory study provides a means for evaluating and rating Telecare medical information systems in order to provide a more effective security solution. This analysis of existing solutions was conducted via an in-depth study of Telecare security. This is a proposition for current biometric technologies as a new means for secure communication of private information over public channels. Specifically, this research was done in order to provide a means for businesses to evaluate prospective technologies from a 3 dimensional view in order to make am accurate decision on any given biometric security technology. Through identifying key aspects of what makes a security solution the most effective in minimizing risk of a patient’s confidential data being exposed we were then able to create a 3 dimensional rubric to see not only from a business view but also the users such as the patients and doctors that use Telecare medical information systems every day. Finally, we also need to understand the implications of biometric solutions from a technological standpoint

A lightweight privacy preserving authenticated key agreement protocol for SIP-based VoIP

Session Initiation Protocol (SIP) is an essential part of most Voice over Internet Protocol (VoIP) architecture. Although SIP provides attractive features, it is exposed to various security threats, and so an efficient and secure authentication scheme is sought to enhance the security of SIP. Several attempts have been made to address the tradeoff problem between security and efficiency, but designing a successful authenticated key agreement protocol for SIP is still a challenging task from the viewpoint of both performance and security, because performance and security as two critical factors affecting SIP applications always seem contradictory. In this study, we employ biometrics to design a lightweight privacy preserving authentication protocol for SIP based on symmetric encryption, achieving a delicate balance between performance and security. In addition, the proposed authentication protocol can fully protect the privacy of biometric characteristics and data identity, which has not been considered in previous work. The completeness of the proposed protocol is demonstrated by Gong, Needham, and Yahalom (GNY) logic. Performance analysis shows that our proposed protocol increases efficiency significantly in comparison with other related protocols

ASCP-IoMT: AI-Enabled Lightweight Secure Communication Protocol for Internet of Medical Things

The Internet of Medical Things (IoMT) is a unification of smart healthcare devices, tools, and software, which connect various patients and other users to the healthcare information system through the networking technology. It further reduces unnecessary hospital visits and the burden on healthcare systems by connecting the patients to their healthcare experts (i.e., doctors) and allows secure transmission of healthcare data over an insecure channel (e.g., the Internet). Since Artificial Intelligence (AI) has a great impact on the performance and usability of an information system, it is important to include its modules in a healthcare information system, which will be very helpful for the prediction of some phenomena, such as chances of getting a heart attack and possibility of a tumor, from the collected and analysed healthcare data. To mitigate these issues, in this paper, a new AI-enabled lightweight, secure communication scheme for an IoMT environment has been designed and named as ASCP-IoMT, in short. The security analysis of ASCP-IoMT is performed in different ways, such as an informal way and a formal way (through the random oracle model). ASCP-IoMT performs better than other similar schemes and provides superior security with extra functionality features as compared those for the existing state of art solutions. A practical implementation of ASCP-IoMT is also performed in order to measure its impact on various network performance parameters. The end to end delay values of ASCP-IoMT are 0.01587, 0.07440 and 0.17097 seconds and the throughput values of ASCP-IoMT are 5.05, 10.88 and 16.41 bits per second (bps) under the different considered cases, respectively. For AI-based Big data analytics phase, the values of computation time (seconds) for decision tree, support vector machine (SVM), and logistic regression are measured as 0.19, 0.23, and 0.27, respectively. Moreover, the different values of accuracy for decision tree, SVM and logistic regression are 84.24%, 87.57%, and 85.20%, respectively. From these values, it is clear that decision tree method requires less time than the other considered techniques, whereas accuracy is high in case of SVM

Identity, location and query privacy for smart devices

In this thesis, we have discussed three important aspects of users\u27 privacy namely, location privacy, identity privacy and query privacy. The information related to identity, location and query is very sensitive as it can reveal behavior patterns, interests, preferences and habits of the users. We have proposed several techniques in the thesis on how to better protect the identity, location and query privacy