Despite numerous research efforts, vehicular networks strive to provide primary facilities for the Internet of Vehicles (IoVs), which are higher data rates, robust connectivity, scalability, security, and privacy facets. In this paper, we proposed a decentralized approach SecEdge to efficiently integrate the Vehicular Cloud’s (V-cloud) concept with the idea of edge-computing in IoV that consider Roadside Connecting Nodes (RSCNs) as an intelligent edge. Furthermore, the heterogeneity and highly dynamic network structure of IoV raise many security and privacy issues while designing the hybrid approach. SecEdge focuses on secure inter-vehicle/intra-vehicle communications using one-way hash functions and secure storage/retrieval of data in/from the upper layer of the architecture. Thus, the system becomes more reliable, safe, and scalable for the drivers as well as the passengers. By providing secure data storage, we can overcome the data leakage problem that occurs due to side-channel attacks and weak security parameters. The qualitative and quantitative analysis depicts that the SecEdge has reduced the computation cost and energy consumption by up to 75% to other state-of-the-art methods. The security analysis provides the formal security proof based on the Random Oracle Model (ROM) and ProVerif tool that shows the security strength in terms of privacy preservation, location tracing, and revocation along with the different security attacks such as man-in-the-middle attack, impersonation, denial-of-service attack, repudiation, replay attack, modification, etc.

The Internet of Vehicles (IoV) faces significant challenges related to secure authentication, efficient communication, and privacy preservation due to the high mobility of vehicles, the need for real-time data processing, varying quality of communication links, and the diverse range of devices and protocols requiring interoperability. These challenges are further complicated by the large-scale, dynamic, and heterogeneous nature of IoV systems. Traditional approaches using Road Side Connecting Nodes (RSCNs) face challenges like limited range, high costs, and single points of failure. Drone-assisted IoV (DIoV) networks address these issues by using Unmanned Aerial Vehicles (UAVs) as mobile edge nodes, enhancing connectivity, extending coverage, and improving adaptability and resilience. To address these challenges, we propose SECURE, a drone-assisted, Physically Unclonable Function (PUF)-based authentication and privacy-preserving protocol integrated with edge computing. This architecture replaces RSCNs with edge nodes and incorporates UAVs as mobile edge nodes, providing extended coverage, reduced latency, and enhanced adaptability. The PUFs in SECURE generate unique hardware-based cryptographic keys, adding an additional layer of security, while edge computing offloads computational tasks, improves network efficiency, and further reduces latency. The formal security analysis, conducted using the Random Oracle Model (ROM), proves the robustness of the session key against active and passive adversaries. Furthermore, informal security analysis demonstrates that SECURE effectively resists various security attacks, while achieving confidentiality, integrity, and authenticity in DIoV. In SECURE, we have considered two types of devices for experiments: NVIDIA Jetson Xavier NX and Raspberry Pi 4. The performance analysis, considering the results from Jetson Xavier NX, demonstrates that SECURE achieves maximum upto approximately 82.1% less communication cost and 78% faster computation time compared to the state-of-the-art schemes.

This paper investigates the feasibility of cache content prediction and coherence in the context of secure communication and search. We introduce a distributed multi-tier mobility-assisted edge intelligence based caching framework for the Internet of Vehicles (IoVs), called CacheIn. The proposed framework leverages user preferences, data correlations, and mobility information to prefetch content to the IoV edge. To enable content management based on mobility, we propose a novel Normalized Hidden Markov Model (NM-HMM) that anticipates a vehicle's future position. The framework also utilizes a mobility-aware collaborative filtering-based federated learning (FL) technique to enhance cache hit, reduce latency, and protect user privacy. To ensure secure cross-domain data sharing and mitigate the risk of data breaches, we also propose an extended ciphertext policy attribute-based encryption (ECP-ABE) mechanism. Compared to content popularity-based caching schemes, CacheIn achieves up to 80%, 38%, and 55% improvement in cache hit ratio for different cache sizes, vehicle densities, and cache lookup scenarios. Moreover, our approach reduces key generation, encryption, and decryption times by 35 %.

The fully dynamic dense environment of the Internet of Vehicles (IoV) and conditions like high traffic jams, collisions, and uneven road conditions increase the communication messages. Consequently, the computation and communication costs of the IoV network are increased. Therefore, IoV needs a lightweight and efficient security solution along with effective communications. Existing state-of-the-art schemes in IoV are generally based on cryptographic methods that use session keys, public keys, elliptic curves, and Message Authentication Codes (MAC). In contrast to the other schemes, MAC-based schemes provide feasible security solutions having high performance with less overhead. The existing MAC-based authentication schemes are vulnerable to the key disclosure issue along with some security attacks such as side-channel attacks, Distributed Denial of Services (DDoS), etc. Due to the side channel attack, a data leakage problem occurs, which is a serious concern in security and privacy facets. We propose a novel MAC-based authentication scheme (NoMAS) that mitigates the above-discussed challenges and provides all the benefits of MAC-based schemes. The NoMAS scheme offers a solution for key disclosure issues by providing Hard Key and Soft Key Updates (HKU and SKU) and data leakage problems using encryption along with high performance. It reduces the computational overhead maximum to 99.60% and the communication overhead maximum to approximately 81% compared to the existing schemes. In the security analysis, We have provided the formal security proof using BAN logic and the ProVerif tool and verified the correctness of the scheme.

Traditional security solutions for the edge have lots of challenges like high power consumption, communication, and computation overhead. These solutions are not feasible for highly dynamic resource-constrained (memory and processing power) Internet of Vehicles (IoV) networks. We can use Physical Unclonable Functions (PUFs) to address this issue. This paper discusses a new PUF-based anonymous mutual authentication and key exchange protocol for the IoV communication environment by combining unique, unpredictable PUFs and one-way hash functions. In the proposed protocol, a three-layered infrastructure, i.e., vehicle layer, edge computing layer, and cloud layer, is used for the IoV networks to make it efficient and improve the throughput and Quality of Service (QoS). The proposed hybrid system provides a security solution for cloning, side-channel and physical attacks along with the less computation and negligible storage cost. The implementation and performance analysis shows that the proposed protocol reduces the computation-communication overhead maximum upto 80% and 60% respectively. It also reduces the time complexity.

Over the period, the universal internet of vehicles (UIo V) has acquired considerable attention in enhancing drive safety, traffic management, infotainment. Due to the heteroge-neous communication, it is highly vulnerable to various types of security and privacy attacks. Security and privacy concerns in the UIo V are commonly addressed with central authentication, in which only the registration authority has the power to authenticate vehicles and other UIo V components. Some of the researchers proposed anonymous authentication techniques to re-move this dependency. However, the existing methods for anony-mous authentication endure a very high computation overhead for the certificate and signature validation process, due to which a high rate of message loss happens. In this paper, we propose a lightweight anonymous authentication scheme called LAAS for UIo V using a bilinear map and lightweight cryptographic operation (i.e., one-way hash function, XOR, concatenation) to achieve a high level of security and privacy. Additionally, we propose an idea of batch message verification. The performance analysis of LAAS demonstrates that it is lightweight and produces an efficient result in terms of computational cost and latency when compared to other existing state-of-the-art schemes for verifying signatures and certificates by holding conditional privacy in UIo V, as demonstrated in this paper.

This paper presents an adaptive self-learning classifier-based clustering algorithm called AlcFier, to support scalability, enhance the stability of the network topology, and provide efficient routing. We incorporate mobility and channel characteristics (i.e., orientation, adjacency, link availability, queue occupancy, and signal-to-noise ratio) into the clustering approach as a channel-aware metric to provide a new direction to the taxonomy of the approaches employed to handle cluster head election, cluster affiliation, and cluster administration challenges. Experimental results show that AlcFier performs efficiently, improves cluster stability, reduces transmission delays, and improves throughput compared with the state-of-the-art routing protocols.

Revolution in the transportation industry was envisioned by self-driving vehicles, with the potential of communication with other vehicles and interaction with other units of the smart environment. With the advent of the Internet of Vehicles(IoV), which is a system that allows communication between vehicles and other static components of the environment and is a convergence of the Internet of Things (IoT), vehicles are considered as an essential part of the network having secure data sensing and processing platforms. Many vehicular ad-hoc networks (VANETs) research focused on the limited set of applications for intelligent transportation systems (ITS) and typically implied safe driving, infotainment, and traffic management. However, it still exhibits an enormous scope of enhancement in various areas of ITS. In this article, we present a new architecture for IoV, keeping in view the different aspects of ITS and discussing how it can mitigate the challenges of secure communication in IoV along with the new visionary solution for authentication. An IoV is highly dynamic, having different topological structures, uneven distribution of nodes, and, therefore, vulnerable to various security and privacy attacks. This article also presents an efficient batch verification scheme having lightweight authentication that uses bilinear map and one-way hash functions to ensure a high level of security within the limited time constraint as compared to single message verification. The proposed scheme has better performance than the existing techniques in terms of computational delay, time complexity, transmission overhead, and energy consumption.

Wireless sensor networks (WSNs) are gaining traction in day to day applications where data has to be gathered in hostile environments using low computing power sensors. As these sensors are deployed in hostile environments, strong authentication mechanisms are essential to guarantee the safety and security of the data being transferred. But, these strong authentication mechanisms are computationally heavy for the low power sensors. So, there is a need for a lightweight and secure authentication protocol for WSNs. Applications of these sensor ranges from healthcare to oil and exploration. The security of the data being gathered and transmitted is of utmost importance as they can correlate to life and death situations in some instances. So, employment of extremely secure schemes is a necessity but all these schemes are computationally very expensive and require powerful hardware. The sensors used in WSN are designed for low power environments, and longevity and hence do not possess these hardware resources to secure the communication. Hardware-level, as well as lightweight operations, have to employ for securing the communication. This procedure also preserves the integrity of data being gathered and transmitted by the sensor through these WSNs.

Ensuring secure transmission over the communication channel is a fundamental responsibility to achieve the implementation objective of universal internet of vehicles (UIoV) efficiently. Characteristics like highly dynamic topology and scalability of UIoV makes it more vulnerable to different types of privacy and security attacks. Considerable scope of improvement in terms of time complexity and performance can be observed within the existing schemes that address the privacy and security aspects of UIoV. In this paper, we present an improvised authentication and lightweight batch verification method for security and privacy in UIoV. The suggested method reduces the message loss rate, which occurred due to the response time delay by implementing some low-cost cryptographic operations like one-way hash function, concatenation, XOR, and bilinear map. Furthermore, the performance analysis proves that the proposed method is more reliable that reduces the computational delay and has a better performance in the delay-sensitive network as compared to the existing schemes. The experimental results are obtained by implementing the proposed scheme on a desktop-based configuration as well as Raspberry Pi 4.

With the rapid technological advancement of the universal internet of vehicles (UIoV), it becomes crucial to ensure safe and secure communication over the network, in an effort to achieve the implementation objective of UIoV effectively. A UIoV is characterized by highly dynamic topology, scalability, and thus vulnerable to various types of security and privacy attacks (i.e., replay attack, impersonation attack, man-in-middle attack, non-repudiation, and modification). Since the components of UIoV are constrained by numerous factors (e.g., low memory devices, low power), which makes UIoV highly susceptible. Therefore, existing schemes to address the privacy and security facets of UIoV exhibit an enormous scope of improvement in terms of time complexity and efficiency. This paper presents a lightweight authentication and batch verification scheme (LABVS) for UIoV using a bilinear map and cryptographic operations (i.e., one-way hash function, concatenation, XOR) to minimize the rate of message loss occurred due to delay in response time as in single message verification scheme. Subsequently, the scheme results in a high level of security and privacy. Moreover, the performance analysis substantiates that LABVS minimizes the computational delay and has better performance in the delay-sensitive network in terms of security and privacy as compared to the existing schemes.