Ensuring trust within the healthcare system and addressing privacy and security challenges in the Internet of Medical Things (IoMT) is of paramount importance. Based on our preliminary analysis results of Masud et al.’s authentication protocol, we propose an improved solution building upon their protocol. Our improved protocol incorporates various security measures to enhance its security. To validate the effectiveness of our improved protocol, we employ a comprehensive range of heuristic and formal security analysis methods. Comparative evaluations with other relevant protocols reveal that our proposed solution achieves satisfactory operational performance in resource-constrained IoMT scenarios.

Very recently, Masud et al. (2022) proposed a lightweight and anonymity-preserving user authentication scheme to establish secure communication between the doctor, the gateway, and sensor nodes in IoT-based healthcare, aiming to ensure the privacy of the patients’ physiological data. In this article, however, we carefully revisit their scheme and first point out that the scheme is not practically implementable in its current form, and second we show that it is vulnerable to session key disclosure attacks, off-line password guessing attacks, and traceability attacks, under the assumption that the attacker can gain access to the sensor nodes and the doctor’s device. We also propose fixes for each of these issues or vulnerabilities.

In this paper, we present a new identity-based encryption IBE scheme using bilinear pairings. Compared with the famous IBE scheme of Boneh and Franklin, ours is more practical in the multiple private key generator multiple-PKG environment. We prove that our scheme meets chosen ciphertext security in the random oracle model, assuming the intractability of the standard bilinear Diffie-Hellman problem. Copyright © 2013 John Wiley & Sons, Ltd.

This paper presents a method to capture the computational intensity and computing resource requirements of data analysis in intelligent transportation systems (ITS). These requirements can be transformed into a generic methodological framework for Cyber-ITS, mainly consisting of region-based ITS data divisions and tasks scheduling for processing, to support the efficient use of cyber-infrastructure (CI). To characterize the computational intensity of a particular ITS data analysis, the computational transformation is performed by data-centric and operation-centric transformation functions. The application of this framework is illustrated by two ITS data analysis cases: multi-sensor data fusion for traffic state estimation by integrating rough set theory with Dempster-Shafer (D-S) evidence theory, and geospatial computation on Global Positioning System (GPS) data for advertising value evaluation. To make the design of generic parallel computing solutions feasible for ITS data analysis in these cases, an approach is developed to decouple the region-based division from specific high performance computer (HPC) architecture and implement a prototype of the methodological framework. Experimental results show that the prototype implementation of the framework can be applied to divide the ITS data analysis into a load-balanced set of computing tasks, therefore facilitating the parallelized data fusion and geospatial computation to achieve remarkable speedup in computation time and throughput, without loss in accuracy.