Abigail Akosua Addobea

The influx of wearable sensor devices has influenced a new paradigm termed wearable health crowd-sensing (WHCS). WHCS enables wearable data collection through active sensing to provide health monitoring to users. Wearable sensing devices capture data and transmit it to the cloud for data processing and analytics. However, data sent to the cloud is vulnerable to on-path attacks. The bandwidth limitation issue is also another major problem during large data transfers. Moreover, the WHCS faces several anonymization issues. In light of this, this article presents a batch processing method to solve the identified issues in WHCS. The proposed batch processing method provides an aggregate authentication and verification approach to resolve bandwidth limitation issues in WHCS. The security of our scheme shows its resistance to forgery and replay attacks, as proved in the random oracle (ROM), while offering anonymity to users. Our performance analysis shows that the proposed scheme achieves a lower computational and communication cost with a reduction in the storage overhead compared to other existing schemes. Finally, the proposed method is more energy-efficient, demonstrating that it is suitable for the WHCS system.

Current trends of mobile technology have seen a tremendous growth in its application in smart healthcare. This has resulted in the adoption and implementation of mobile health (m-health) systems by providing health assistance to the aging population. Despite its advantageous benefits, its computational complexities cannot be overlooked. M-health devices are portable processing tiny equipment with limited computational capabilities thereby making them complex for the implementation of public key cryptosystems. In spite of this, an Offline-Online signature scheme called the MHCOOS has been proposed to solve the difficulties in the computational ability. The scheme enjoys the following benefits by splitting the signing part into both offline and online phases. The offline phase performs heavy computations when a message is absent, whereas lighter computations are performed at the online stage when a message is present. Secondly, the online computations are extremely fast due to the already computed offline signature value and lighter pairings involved. Our performance analysis demonstrates how the proposed scheme outperforms other schemes. Finally, the hardness of the scheme is proven under the Bilinear Diffie–Hellman (BDH) and Computational Diffie–Hellman (CDH) problem in the random oracle model.