A significant evolution in healthcare recently uses technological advancements to perform different activities, such as patient electronic medical records (EMRs) data gathering, preserving, processing, diagnosis, and handling. The adaptation of the Internet of Things (IoT) and cloud has further facilitated the enhancement of related healthcare systems, which can considerably improve data connectivity, accessibility, and exchange, which leads to a significant improvement in the quality of services to patients. Furthermore, scientific computations over data in transmission can be exposed to adversaries and may reveal private data for financial benefit. This article uses the Cheon-Kim-Kim-Song fully homomorphic encryption scheme and IOTA Tangle using masked authenticated messaging (MAM) protocol to provide secure communication between patient and doctor. CKKS-FHE-based data encryption provides data privacy, and secured EMRs sharing through IOTA Tangle guarantees data confidentiality. The performance of this work is analyzed in terms of encryption and decryption time, and payload sharing using MAM and NON-MAM protocols results in evidence of the effectiveness of the approach and improves overall security. The proposed scheme performs better overall computation time and performance than other relevant schemes. Further, the security analysis shows that the proposed system is resilient to data immutability and integrity, forward secrecy, and passive and active attacks.

The advent of group-oriented communication applications has triggered research on secure group communication (SGC) in vehicular ad hoc networks (VANETs). Given this, some researchers worked in this area and proposed various schemes. However, these systems lacking the dynamic nature, and struggling with larger processing loads, enormous storage, increased communications, security, and privacy concerns. Further, with the increase in the size of VANET, it is challenging to manage processing loads and storage requirements of group controller (GC)-centric group key agreement (GKA). To address these drawbacks in existing VANET communications, we propose a blockchain IOTA sharding-based smart contract-centric GKA for SGC in large VANETs. In this scheme, we partition the main network into${r}$sharded subnetworks using blockchain sharding technique, with$G_{1}, G_{2}, G_{3},\ldots, G_{r}$as smart contract (SC) instances generated by GC, G, which functions as Sub-GC (Sub-GC) to their respective shards. Under the Elliptic curve decision Diffie–Hellman (ECDDH) and group-Elliptic curve Diffie-Hellman (GECCDH) assumptions, the proposed protocol is proven to be secure. The suggested protocol outperforms the other protocols for secure communication in large VANETs, according to the performance analysis.

Summary The significance of prisoner's dilemma in making two completely rational individuals might not cooperate even their best interest to do so. Every criminal investigation is strongly reliant on crime data classification and optimization. In this work, we extended prisoners' dilemma for crime data classification and its optimization. A confusion matrix‐based optimization technique for crime data with game theory model in order to identify the person involvement in crime is to be predicted and clustered them into confess, not confessed, and indeterministic states based on the neutrosophic logic principle. In this technique, first we map neutrosophic logic into crime system to break the uncertainties in crime clustering. Next, we preliminary cluster the crime data pairs that indicates two offenders neutrosophic values into three clusters. However, some pairs lie in intersections of two or three clusters. So we optimize the clustering into disjoint clusters will be done based on the ratio of intra‐cluster and inter‐cluster distances. We have implemented the proposed method. The experimental result shows that the quality of proposed method based on accuracy, precision, and recall parameters, observed more than 90% accuracy.

Summary Group key management with privacy preserving and trust still remains a precarious and stimulating issue for securing multicast communications in an energy embarrassed large wireless ad‐hoc networks (WANETs). To address this, few researchers with the adaption of blockchain technology and practical usage of a privacy‐preserving smart contract as group controller made these group key agreements adaptable to WANET. However, proportionate to the increase in the size of the group, the processing load on the smart contract is also increasing, which made the capability of the smart contract could not work beyond a certain group size. Contemporary blockchain schemes suffer from various inherent shortcomings in their latency, scalability, and processing throughput. So, in this direction, we adopted blockchain sharding smart contract‐centric processing for making the key agreement adaptable to large WANETs. In this technique, we divide the large network intorsharded subnetworks withG1,G2,G3, …,Gras smart contract instances generated by group controllerG, which acts as subgroup controllers to their respective shards using blockchain sharding technique. This protocol is shown secure under the assumptions elliptic curve decision Diffie–Hellman and group‐elliptic curve Diffie–Hellman. The performance analysis demonstrates that the proposed protocol is highly proficient than examined protocols for secure communication in large WANETs.

Abstract With recent developments in hyperelliptic curve cryptographic system (HECC) processing and the proposed work, the myth that HECC is not suited for practical applications in constrained networks is dispelled. This article proposes dynamic authenticated contributory group key agreement (DACGKA) protocol using HEC‐DH. The DACGKA is less costly and ideally appropriate for resource‐restricted networks such as VANETs, MANETs, and WSNs because of its lesser key sizes and advancements in operational processing. The suggested protocol is implemented across a finite field using an HEC of genus 1 (ECC), genus 2, and genus 3, with promising results, including a significant reduction in key size and exchange overhead, an increase in key safety, and a broader range of applicability. According to a comparison of the proposed approach on different genus curves, HECC over genus 2 with a suitable key length can be applied for memory and power restricted devices to increase data secrecy and system efficiency. Further, HECC can outperform ECC for low‐cost, secure group communication applications. As a part of security analysis, first, we proved that each coordinate of HEC‐DH secret value is as hard as the entire DH value, and then concrete security proofs based on the HEC‐DLP were established.

Patient safety is a global public health concern nowadays, especially in elderly people who need physiological health monitoring systems integrated with a technology which will help to oversee and manage the medical needs. In this direction, we propose a lightweight effective healthcare monitoring system designed by using the Internet of Things (IoT) and Radio Frequency Identification (RFID) tags. In this technique, we use dual-band RFID protocols which are the one working at a high frequency of 13.56 MHz and useful to figure out the individuals, and 2.45 GHz microwave bands are used to monitor corporal information. Sensors are used to monitor and collect patient physiological data; RFID tag is used to recognize the patient. This IoT-based RFID healthcare monitoring system provides acquisition of physiological information of elderly people and patients in hospital. Further, it is aiming to secure patient’s health recordings using hyper elliptic curve- (HEC-) based signcryption algorithm while allowing the doctor to access patient health information. Privacy is provided to variable length patient medical records using different genus curves, and the evaluation shows that the proposed algorithm is optimal with respect to healthcare.