Abstract

Healthcare 5.0 is a system that can be deployed to provide various healthcare services. It does these services by utilising a new generation of information technologies, such as Internet of Things (IoT), Artificial Intelligence (AI), Big data analytics, blockchain and cloud computing. Due to the introduction of healthcare 5.0, the paradigm has been now changed. It is disease-centered to patient-centered care where it provides healthcare services and supports to the people. However, there are several security issues and challenges in healthcare 5.0 which may cause the leakage or alteration of sensitive healthcare data. This demands that we need a robust framework in order to secure the data of healthcare 5.0, which can facilitate different security related procedures like authentication, access control, key management and intrusion detection. Therefore, in this review article, we propose the design of a secure generalized healthcare 5.0 framework. The details of various applications of healthcare 5.0 along with the security requirements and threat model of healthcare 5.0 are provided. Next, we discuss about the existing security mechanisms in healthcare 5.0 along with their performance comparison. Some future research directions are finally discussed for the researchers working in healthcare 5.0 domain.

Abstract

Dynamic charging is a potential technology that would enable electric vehicles to be charged while they are in motion. Significant security and privacy concerns, on the other hand, arise as a result of communications between electric vehicles and a variety of dynamic charging system entities occurring over a public channel. Numerous authentication protocols have been presented recently to address security concerns associated with dynamic charging system. Nonetheless, we provide a lightweight authentication protocol suite that enables mutual authentication and session key agreement between the electric vehicle and the charging system while safeguarding against numerous attacks. The EV-PUF is based on physical unclonability, which is gaining popularity as a substitute for ultra-lightweight authentication and resistance to machine learning based attacks. Additionally, the security of the EV-PUF suite has been demonstrated using the random oracle model and state-of-the-art tool, Tamarin. According to the performance analysis, it is apparent that the EV-PUF suite improves efficiency in terms of consumption of less communication and computing overhead.

Abstract

Smart healthcare technologies transform the tradi- tional healthcare system in all possible ways. Smart healthcare has enormous number of benefits over the traditional system. However, at the same time, it also suffers from some healthcare data security and privacy related issues as the potential Internet attackers may get access to the sensitive healthcare through the deployment of various kinds of attacks. To mitigate these issues, in this paper, a new lightweight remote user authentica- tion and key establishment scheme (in short, UAKM-SH) has been proposed by making the use of lightweight cryptographic operations. The security analysis of UAKM-SH is conducted to prove its robustness against various possible attacks. A detailed comparative study among the proposed UAKM-SH and other ex- isting schemes shows that UAKM-SH performs better in terms of computation cost, communication cost, and the offerered security and functionality features. Finally, the testbed implementation of UAKM-SH is given to observe its behaviour in the real time scenario. Index Terms—Smart healthcare, authentication, key agree- ment, security, testbed implementation.

Abstract

Parallel computing of hash functions along with the security requirements have great advantage in order to reduce the time consumption and overhead of the CPU. In this article, a keyed hash function based on farfalle construction and chaotic neural networks (CNNs) is proposed, which generates a hash value with arbitrary (defined by user) length (eg, 256 and 512 bits). The proposed hash function has parallelism merit because it is built over farfalle construction which avoids the dependency between the blocks of a given message. Moreover, the proposed hash function is chaos based (ie, it relies on chaotic maps and CNNs which have non-periodic behavior). The security analysis shows that the proposed hash function is robust and satisfies the properties of hash algorithms, such as random-like (non-periodic) behavior, ideal sensitivity to original message and secret key, one-way property and optimal diffusion effect. The speed performance of the hash function is also analyzed and compared with a hash function which was built based on sponge construction and CNN, and compared with secure hash algorithm (SHA) variants like SHA-2 and SHA-3. The results have shown that the proposed hash function has lower time complexity and higher throughput especially with large size messages. Additionally, the proposed hash function has enough resistance to multiple attacks, such as collision attack, birthday attack, exhaustive key search attack, preimage and second preimage attacks, and meet-in-the-middle attack. These advantages make it ideal to be used as a good collision-resistant hash function.

Abstract

With the ongoing revolutionary growth of the industrial Internet of Things and smart grid networks, smart grid (SG) communication has been acknowledged as a next-generation network for intelligent and efficient electric power transmission. In SG networks, smart meters (SMs) generally send requests for electricity demand to service providers (SPs), which deal with the requests for efficient energy distribution. However, SGs experience many security issues with the deployed SMs and untrusted wireless communication. To tackle these security issues, we propose a privacy-preserving authentication scheme for demand response management in SGs, called BPPS. It can resist various attacks and achieve secure mutual authentication with key agreement; moreover, it provides integrity of demand-response data using blockchain. Moreover, we perform the informal and formal (mathematical) security analysis to confirm that BPPS is secure against various attacks and achieves session key security, respectively. Furthermore, we conduct the performance and simulation analysis for SGs

Abstract

The deployed vehicles in an Internet of Vehicles (IoV) can take intelligent decisions by means of exchanging the real- time traffic-related information between the vehicles and IoV in- frastructures. This further reduces the probability of the traffic jams and accidents. However, the insecure (public) communication among the various entities in IoV makes various security threats and attacks that can be launched by passive/active adversaries present in the network. In view of this context, there is a need of an efficient cryptographic primitive which can produce single compact signature. A multi-signature scheme (MSS) empowers a collection of signers to conjointly sign a given message using a single compact signature that can be verified by any verifier. Herein, we put forward a new identity-based multivariate MSS, namely MV-MSS, which is built on top of the intractability of multivariate-quadratic (MQ) problem. The fact is that multivariate public key cryptosystem provides fast, post-quantum safe and effi- cient primitives, which makes it the front runner candidate among the post-quantum cryptographic candidates. MV-MSS is proven to be secure in the existential unforgeability under chosen-message and chosen identity attack model if solving the MQ problem is NP-hard. We then incorporate the designed MV-MSS in IoV ap- plication where the leader (cluster head) selected from a group of vehicles in a dynamic cluster forms the multi-signatures on the messages securely received from its member vehicles. Later, the messages along with their multi-signatures are forwarded to the nearby road-side unit (RSU) of the cluster head, which are then for- warded to a cloud server in the blockchain center maintained by a Peer-to-Peer (P2P) cloud servers network. In this way, the messages

Abstract

With rapid advancements in the technology, almost all the devices around are becoming smart and contribute to the Internet of Things (IoT) network. When a new IoT device is added to the network, it is important to verify the authenticity of the device before allowing it to communicate with the network. Hence, access control is a crucial security mechanism that allows only the authenticated node to become the part of the network. An access control

Abstract

Smart devices in an Internet of Things (IoT) gen- erate a massive amount of big data through sensors. The data is used to build intelligent applications through machine learn- ing (ML). To build these applications, the data is collected from devices into data centers for training ML models. Usually, the training of models is performed on central server, but this approach requires the transfer of data from devices to central server. This centralized training approach is not efficient because the users are much less likely to share data to the centralized data centers due to privacy issues and bandwidth limitations. To mitigate these issues, we propose an efficient hybrid secure fed- erated learning approach with the blockchain to securely train the model locally on devices and then to store the model and its parameters into the blockchain for traceability and immutabil- ity. A detailed security and performance analysis is presented to show the efficacy of the proposed approach in terms of security, resilience against many security attacks, and cost effectiveness in computation and communication as compared to other existing competing schemes. Index Terms—Authentication, big data analytics, blockchain, Internet of Things (IoT), key agreement, security.

Abstract

Precision farming has a positive potential in the agricultural industry regarding water conservation, increased productivity, better development of rural areas, and increased income. Blockchain technology is a better alternative for storing and sharing farm data as it is reliable, transparent, immutable, and decentralized. Remote monitoring of an agricultural field requires security systems to ensure that any sensitive infor- mation is exchanged only among authenticated entities in the network. To this end, we design an efficient blockchain-enabled authenticated key agreement scheme for mobile vehicles-assisted precision agricultural Internet of Things (IoT) networks called Agr oM obi Bl ock. The limited existing work on authentication in agricultural networks shows passive usage of blockchains with very high costs. Agr oM obi Bl ock proposes a novel idea using the elliptic curve operations on an active hybrid blockchain over mobile farming vehicles with low computation and communica- tion costs. Formal and informal security analysis along with the formal security verification using the Automated Validation of Internet Security Protocols and Applications (AVISPA) software tool have shown the robustness of Agr oM obi Bl ock against man-in-the-middle, impersonation, replay, physical capture, and ephemeral secret leakage attacks among other potential attacks. The blockchain-based simulation on large-scale nodes shows the computational time for an increase in the network and block size

Abstract

Vehicular ad-hoc networks (VANETs) are increasingly commonplace, partly due to the popularity of electric vehicles and the digitalization of cities. Data collected and shared in VANETs include traffic-related information, such as those relating to real-time traffic situations and road works. In recent times, there has been a trend of moving away from a centralized approach to a decentralized approach, for example, using Blockchain to facilitate secure data sharing and traceability of critical information. Hence, in this paper, we comprehensively survey the existing literature on blockchain-based VANET systems, focusing on the application of different blockchain technologies in different contexts, as well as the associated challenges and research opportunities.