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.

SUMMARY Privacy‐preserving data publishing (PPDP) provides scope for performing various types of analytics by the researcher on the published data without revealing the individuals' privacy. However, it is necessary to consider the data from all the available locations to obtain accurate results from the published data. Then only the derived associations from the published data are helpful to make new decisions by an organization. Existing PPDP models on multiple sensitive attributes like KC‐slice (K stands for bucket size, C stands for constant threshold), KCi‐slice (K–bucket size, Ci–variable threshold), Novel KCi‐slice, and Optimal KCi‐slice models are concentrated only when data is located at a single location. This research work introduces a new model called “distributed KCi‐slice,” which considers the data with multiple sensitive attributes from various locations to obtain accurate results. Initially, this model proposes a novel technique called a distributed algorithm to merge the different data sets into a single data set. It combines the data differently, so that it is not possible to identify any record of a specific data set from the merged data. The proposed model also uses a new bucketization algorithm named (l,m,d)*‐anonymity (l stands for distinct semantic categories of the sensitive values of a sensitive attribute in a specific bucket, m stands for the number of sensitive attributes, and d stands for different sensitive categories for the sensitive values of a sensitive attribute in each sensitive bucket) for the bucketization of the tuples into the buckets. It imposes the privacy constraints only on high sensitive values of each sensitive attribute by considering the semantic and sensitive levels of sensitive values. The distributed KCi‐slice model finally publishes the data in the form of multiple sensitive tables and one quasi table. This model is implemented based on attribute sensitiveness to enhance the utility and privacy levels of the published data.

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.

This paper proposes a new two round authenticated contributory group key agreement (ACGKA) protocol based on elliptic curve Diffie–Hellman (ECDH) with integrated signature. In this technique, one node is picked up as the group controller, and this node runs an authenticated ECDH with the rest of the nodes to generate an authenticated shared key per each two-party. It then merges these keys in another round in such a way that every member obtains the identical authenticated group key. Further, ACGKA is extended to dynamic ACGKA protocol. The dynamic ACGKA, being elliptic curve decisional Diffie Hellman-based, is less expensive and well suited for resource constrained networks such as mobile ad-hoc networks, and wireless sensor network. Also, we demonstrate that all the protocols proposed in this paper are provably secure in the standard model under ECDDH assumption and moreover secure against most of the active and passive attacks. Finally, the proposed protocol is compared with other prevalent ECDH and Diffie Hellman based group key agreement protocols, and results are found to be satisfactory. Copyright © 2015 John Wiley & Sons, Ltd