Secure RFID-Assisted Authentication Protocol for Vehicular Cloud Computing Environment

The ever-evolving Internet of Things (IoT) has ushered in a new era of intelligent manufacturing across multiple industries. However, the security and privacy of real-time data transmitted over the public channel of the Industrial IoT (IIoT) remain formidable challenges. Existing lightweight protocols often omit one or more critical security features, such as anonymity and untraceability, and are susceptible to threats like desynchronization attacks. Additionally, they struggle to achieve an optimal balance between robust security and performance efficiency. To bridge these gaps, we introduce a new lightweight key agreement security scheme that guarantees secure access to the IIoT-enabled flexible manufacturing system (FMS). The strength of our scheme lies in its utilization of the authenticated encryption with associative data (AEAD) primitive, AEGIS, along with hash functions and physical unclonable functions, which secure the IIoT ecosystem. Additionally, our scheme offers flexibility in the form of the addition of new machines, password updates, and revocation in cases of theft or loss. A comprehensive security analysis demonstrates the efficacy of the proposed scheme in thwarting various attacks. The formal analysis, based on the Real-or-Random (RoR) model, ensures session key indistinguishability, while the informal analysis highlights its resilience against known attacks. The comparative assessment demonstrates that the proposed scheme consistently outperforms the benchmark schemes across multiple dimensions, including security and functionality features, computational and communication overheads, and runtime efficiency. Specifically, the proposed scheme achieves peak performance enhancements of 77.55%, 44.73%, and 69.6% in computational overhead, runtime overhead, and communication overhead, respectively, underscoring its substantial performance advantages.

Recently, Vehicular Ad Hoc Networks (VANET) have attracted the attention of research communities, leading car manufacturers, and governments due to their potential applications and specific characteristics. Their research outcome was started with awareness between vehicles for collision avoidance and Internet access and then expanded to vehicular multimedia communications. Moreover, vehicles’ high computation, communication, and storage resources set a ground for vehicular networks to deploy these applications in the near future. Nevertheless, on-board resources in vehicles are mostly underutilized. Vehicular Cloud Computing (VCC) is developed to utilize the VANET resources efficiently and provide subscribers safe infotainment services. In this chapter, the authors perform a survey of state-of-the-art vehicular cloud computing as well as the existing techniques that utilize cloud computing for performance improvements in VANET. The authors then classify the VCC based on the applications, service types, and vehicular cloud organization. They present the detail for each VCC application and formation. Lastly, the authors discuss the open issues and research directions related to VANET cloud computing.

A secure and efficient AKE scheme for IoT devices using PUF and cancellable biometrics

Abstract. The increased deployment of Internet of Things (IoT) has revolutionized global connectivity through applications such as smart cities, smart industries, healthcare systems, and industrial automation. However, resource-constrained IoT devices face severe security challenges, particularly in device authentication. Traditional authentication mechanisms based on symmetric and asymmetric cryptography introduce excessive communication and computation overhead, making them unsuitable for constrained IoT environments. In this paper, we propose a secure and lightweight device authentication mechanism based on digital certificates from a global stochastic perspective. The proposed framework considers the dynamic and uncertain behavior of IoT networks while ensuring secure identification and communication. The protocol employs asymmetric cryptography, hash functions, nonces, and timestamps to prevent impersonation, replay, and device capture attacks. The security properties of the proposed protocol are formally verified using the AVISPA tool under the Dolev-Yao attacker model. Performance evaluation demonstrates low communication, storage, and computational overhead, making the proposed mechanism suitable for Industrial IoT, smart cities, defense systems, and other mission-critical IoT applications.

With the increased number of vehicles, the traditional VANETs (Vehicular Ad-hoc Networks) experiencing new face transitions. One such concept is Vehicular Cloud Computing (VCC), where the data exchanges between vehicles or any entities, in traffic condition or in an emergency situation can be easily done. Establishing authentication and secure communication in VCC is a major problem because of the highly dynamic nature of vehicles. False messages may mislead the drivers which may cause serious issues. In this paper, we propose a lightweight protocol for authentication and secure communication in the VCC. More specifically, we design a lightweight protocol with hash operations, XORs, concatenations, etc., to ensure security. In-depth security analysis is done to check various attacks in the VCC system. In addition to that, we have done hardware implementation on a desktop computer, on a small single board computer-Raspberry Pi and verified the execution time needed. The performance analysis reveals that our protocol outperforms well in different scenarios like communication cost, storage overhead, computation time, and energy consumption.

Despite the surge in Vehicular Ad Hoc NETwork (VANET) research, future high-end vehicles are expected to under-utilize the on-board computation, communication, and storage resources. Olariu et al. envisioned the next paradigm shift from conventional VANET to Vehicular Cloud Computing (VCC) by merging VANET with cloud computing. But to date, in the literature, there is no solid architecture for cloud computing from VANET standpoint. In this paper, we put forth the taxonomy of VANET based cloud computing. It is, to the best of our knowledge, the first effort to define VANET Cloud architecture. Additionally we divide VANET clouds into three architectural frameworks named Vehicular Clouds (VC), Vehicles using Clouds (VuC), and Hybrid Vehicular Clouds (HVC). We also outline the unique security and privacy issues and research challenges in VANET clouds.

Traditional Complex Event systems (CEP) did not consider the computation requirements of continuous dynamic behavior such as differential equations. In addition, the event composition rules were predefined before the CEP engine began working. The rule defining task is error-prone and cumbersome. In this paper, therefore, a hybrid complex event service is proposed, which deals with not only discrete events but also continuous behavior computation based on IoT (Internet of Things) resource models. In order to satisfy the real-time constraints of processing IoT events, a divide-and-conquer principle is adopted, where we give a combination theorem such that different events can be processed on different IoT resources and then these processed results can be combined to derive complex events. Based on the formal IoT resources and event knowledge, we define interest goals to direct event composition without enumerating event relation to define event composition rules. We finally present event composition algorithms and evaluation to show our idea.

Vehicular Cloud Computing (VCC) facilitates the customers to share resources ranging from storage to computing power to renting it to other users over the internet. VCC technology is combination of VANET and cloud computing. However, this integration of vehicular network and cloud computing introduces new challenges for the research community. For security reasons, users would like to verify the integrity of their data once storing it in the VCC. In this paper, we will introduce a scheme for the integrity checking with the support of the Road Side Unit (RSU) for dynamic vehicular cloud. The hash functions and signatures are employed for integrity checking of messages which are uploaded from the vehicle to the cloud. We have analysed effectiveness of proposed scheme against typical attacks like tampering attack, node impersonation and application attack etc. Extensive simulations are conducted to verify the performance of the proposed scheme and the results are compared with existing research based on ID-based cryptographic scheme. The proposed scheme performs better in terms of computation cost and communication cost.

A survey on vehicular cloud computing

A hybrid scheme for multicast authentication over lossy networks

Integration of IoT and edge cloud computing for smart microgrid energy management in VANET using machine learning

The vehicular cloud computing is an emerging technology that changes vehicle communication and underlying traffic management applications. However, cloud computing has disadvantages such as high delay, low privacy and high communication cost, which can not meet the needs of real-time interactive information of Internet of vehicles. Ensuring security and privacy in Internet of Vehicles is also regarded as one of its most important challenges. Therefore, in order to ensure the user information security and improve the real-time of vehicle information interaction, this paper proposes an anonymous authentication scheme based on edge computing. In this scheme, the concept of edge computing is introduced into the Internet of vehicles, which makes full use of the redundant computing power and storage capacity of idle edge equipment. The edge vehicle nodes are determined by simple algorithm of defining distance and resources, and the improved RSA encryption algorithm is used to encrypt the user information. The improved RSA algorithm encrypts the user information by reencrypting the encryption parameters . Compared with the traditional RSA algorithm, it can resist more attacks, so it is used to ensure the security of user information. It can not only protect the privacy of vehicles, but also avoid anonymous abuse. Simulation results show that the proposed scheme has lower computational complexity and communication overhead than the traditional anonymous scheme.

In vehicular networks, drones can enhance performance by enabling real-time data collection, traffic monitoring, and communication optimization. However, due to the large, open, and highly dynamic nature of vehicular networks, ensuring security and achieving lightweight privacy protection are pressing challenges. Additionally, in traditional solutions, the control center (CC) often performs many tasks, leading to excessive computation and communication overhead, creating a system bottleneck. To address these issues, this paper proposes a privacy-preserving authentication scheme for FL in drone-assisted vehicular networks, where model parameter collection and model training are performed by drones in a privacy-preserving manner, significantly reducing the computation and communication overhead on the CC side. Moreover, the proposed scheme ensures strong privacy protection and efficient authentication by using federated learning, Elliptic Curve Cryptography (ECC), and the Chinese Remainder Theorem (CRT). The performance evaluation results show that the proposed scheme achieves a 17.3% reduction in computation overhead and a 22.8% reduction in communication overhead compared to existing solutions, highlighting its significant advantages.

Vehicular adhoc network (VANET) has a significant potential in reducing traffic congestion to provide a stress-free and safer platform for road drivers to travel on the road. However, the current VANET is vulnerable to several challenges which need to be overcome. Congestion control is considered as one of the main challenges in VANET due to the high dynamic topology characteristic. Reliable congestion control (CC) are necessary to provide effectient dissemination of time-critical safety messages in VANET applications; safety and non-safety applications. In this paper, we present the overview on VANET, its application and challenges. We also discuss on the congestion control and provide a brief survey on the congestion control algorithms such as vehicular cloud computing, multiplicative rate decreasing algorithm, multi-objective Tabu search, D-FPAV algorithm and beaconing strategies which have been proposed in order to provide better solutions towards achieving a successful Smart Tranporation System.

We acquire or provide most of the services with the help of the Internet in the fast-growing world. We should deploy various kinds of systems globally so that other users can practice the same effortlessly, and use storage framework to provide conveniences world-wide effectively. Nowadays, we practice vehicular communication technology to exchange diversified data for varied intentions, which helps vehicle operators in diversified manners such as traffic awareness, weather conditions, road assistance, automatic toll payment system, etc. In this chapter, we converse about data transmission through vehicular ad-hoc networks, cloud computing in the vehicular technology. After that, we survey of different schemes related to secure routing and geo-location details of vehicles. We illustrate concerning security demands, possible attacks, and challenges in the vehicular cloud computing (VCC) architecture. Conclusively, we suggest a new identification scheme to get access of the VCC system from the user end, which can be secured against varied attacks. Moreover, we do analysis of the suggested system to determine security worthiness and measure total required time to execute the phases.