Unmanned Aerial Vehicles (UAVs) have become integral to numerous applications, prompting research towards enhancing their capabilities. For time-critical missions, minimizing latency is crucial; however, current studies often rely on sending data to ground station or cloud for processing due to their limited onboard capacities. To leverage the networking capabilities of UAVs, recent research focuses

In maritime data collection scenarios, due to the constraints of wireless communication and environmental factors such as wave motion, sea surface ducting effects, and sea surface curvature, floating sensor nodes are unable to establish direct data transmission links with the base station. The advent of unmanned aerial vehicle (UAV)-assisted Maritime Internet of Things (MIoT) provides a feasible solution

The security issues in Vehicle Ad Hoc Networks (VANETs) are prevalent within Intelligent Transportation Systems (ITS). To ensure the security of vehicle-to-infrastructure (V2I) communication, extensive research on V2I authentication has been conducted in recent years. However, these protocols often overlook the limitations of communication range, leading to failures in V2I communication. Consequently

The computation-intensive situational awareness (SA) task of unmanned aerial vehicle (UAV) is greatly affected by its limited power and computing capability. To solve this challenge, we consider the joint communication and computation (JCC) design for UAV network in this paper. Firstly, a multi-objective optimization (MOO) model, which can optimize UAV computation offloading, transmit power, and local

Vehicle Edge Computing improves the Quality of Service of vehicular applications by offloading tasks to the VEC server. However, with the continuous development of computation-intensive vehicular applications, the limited resources of the VEC server will not be enough to support these applications. Volunteer Computing-Based Vehicular Ad-hoc Networking (VCBV) proposes a concept of using vehicles as

This paper delves into the performance evaluation of a non-orthogonal multiple access (NOMA) enabled vehicle-to-vehicle (V2V) communication system empowered by simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RIS). Herein, we consider that a moving access point (AP) transmits superimposed signals to nearby and distant NOMA vehicles simultaneously via reflection and

This paper studies a fixed-wing unmanned aerial vehicle (UAV) assisted mobile relaying network (FUAVMRN), where a fixed-wing UAV employs an out-band full-duplex relaying fashion to serve a ground source-destination pair. It is confirmed that for a FUAVMRN, straight path is not suitable for the case that a huge amount of data need to be delivered, while circular path may lead to low throughput if the

Autonomous vehicles safeguard the security and efficiency of Internet of Vehicles systems in small industrial parks by authenticating and exchanging real-time information with transportation infrastructure. Deploying a multi-server framework reduces the risk of message blocking and privacy information leakage from centralized services. However, in traditional handover authentication protocols, there

Vehicular ad hoc network (VANET) has been a promising technology in smart transportation system, which can enable information exchange between vehicles and roadside units (RSUs). However, the privacy of vehicles and RSUs is a critical challenge in VANET, as they may expose sensitive information to malicious attackers or unauthorized parties. Many existing authenticated key agreement (AKA) schemes aim

The utilization of autonomous vehicles is experiencing a rapid proliferation in contemporary society. Concurrently, with the relentless evolution of technology, the inexorable integration of autonomous vehicles into urban environments, driven by the overarching paradigm of smart cities, becomes increasingly apparent. This escalating reliance on autonomous vehicles concurrently heightens the susceptibility

Vehicles of today are composed of over 100 electronic embedded devices known as Electronic Control Units (ECU), each of which controls a different component of the vehicle and communicates via the Controller Area Network (CAN) bus. However, unlike other network protocols, the CAN bus communication protocol lacks security features, which is a growing concern as more vehicles become connected to the

Due to the high mobility, high chance of line-of-sight (LoS) transmission, and flexible deployment, unmanned aerial vehicles (UAVs) have been used as mobile edge computing (MEC) servers to provide ubiquitous computation services to mobile users (MUs). However, the limited energy storage, caching capacity, and computation resources of UAVs bring new challenges for UAV-aided MEC, e.g., how to recharge

In this paper, we consider a multi-tier cellular network in which a hovering Unmanned Aerial Vehicle (UAV) assists the network in the absence of the terrestrial Macrocell base station. The orthogonal sub channels are assumed for communication between the UAV and its attached users. The Femtocell users and Device-to-Device (D2D) pairs transmit their data to the corresponding receivers in the same sub-channels

The rapid development of vehicular ad-hoc networks (VANETs) has brought great convenience to intelligent transportation, and the secure transmission of information in VANETs has become a serious problem. In addition, the protection of private information of vehicles is also a key issue. Aiming at the problem of how to guarantee the secure transmission of information in VANETs under the condition of

With the rapid development and extensive application of unmanned aerial vehicles (UAVs), the issue of UAV swarm network security has become prominent. To protect the security of UAV swarm networks, effective network security defense measures are crucial. One key aspect is the assessment and monitoring of the network's security situation. However, most existing research focuses on the security of individual

Physical layer security (PLS) aims to ensure the confidentiality and authenticity of transmitted data by capitalizing on the inherent randomness of wireless channels. Owing to the popularity of intelligent transportation systems (ITSs), PLS research has sparked renewed interest in the wireless research community. This paper investigates the performance of secure communication in the context of a vehicle-to-vehicle

In recent years, flying ad hoc networks (FANET), formed from unmanned aerial vehicles (UAVs), have absorbed the attention of academic and industrial research communities due to their many applications in military and civilian fields. FANETs benefit from unique features, including highly moving UAVs and dynamic topological structure. Therefore, most existing routing protocols, such as the greedy perimeter

The integration of Internet of Things (IoT) technologies into the vehicular industry has initiated a new era of connected and autonomous vehicles, revolutionizing transportation systems. However, this transformation introduces significant challenges, especially in 5 G networks, such as achieving Ultra-Reliable Low-Latency Communications (URLLC) and maintaining energy efficiency within the high mobility

As connected and autonomous vehicles proliferate, the Controller Area Network (CAN) bus has become the predominant communication standard for in-vehicle networks due to its speed and efficiency. However, the CAN bus lacks basic security measures such as authentication and encryption, making it highly vulnerable to cyberattacks. To ensure in-vehicle security, intrusion detection systems (IDSs) must

A secure authentication framework based on blockchain and ensemble learning is proposed to address the problem that vehicle identity privacy data in Internet of Vehicles (IoV) is vulnerable to theft and tampering. First, a secure and efficient authentication method based on blockchain and Physical Unclonable Function (PUF) is implemented, which ensures the identity privacy of the vehicle when accessing

The future of autonomous transportation systems depends on energy sustainability and secure information exchange from low-power vehicular sensors, hence the increased interest in vehicular sensor charging using simultaneous wireless information and power transfer (SWIPT). This study investigates the physical layer security of a SWIPT-based radio frequency energy harvesting cooperative vehicular relaying

Communication is essential for Cooperative Intelligent Transportation Systems (C-ITS) to achieve better road efficiency, especially for Autonomous Intersection Management (AIM) which coordinates vehicles to pass the intersection safely and efficiently. Communication delays cause severe safety crises (i.e., collisions) and vehicular-performance degradation regarding intersection capacities and vehicular

IoT-based UAV networks comprise interconnected UAVs outfitted with sensors and microcontrollers to simplify data exchange in environments such as smart cities. In light of open-access communication landscapes, IoT-based UAV networks could pose security challenges, encompassing authentication vulnerabilities and the inadvertent disclosure of location and other confidential information to unauthorised

The wireless signal that intentionally disrupts the communication is described as the jamming signal. Clustered jamming is the use of jamming signals of the devices that are clustered in groups, whereas non-clustered jamming refers to the use of the jamming signals of the spatially distributed devices that are un-clustered. The efficiency of the unmanned aerial vehicle (UAV)-assisted cellular networks

With the prevalence of intelligent driving, the vehicular data corresponding to driving safety and traffic management efficiency is widely applied by the Internet of Vehicles (IoV) applications. Vehicular data is shared frequently in IoV, leading to privacy leakage of the message sender, yet most privacy-preserving measures bring difficulties for receivers to detect malicious messages. To trade-off

This study proposes an integrated system that combines energy harvesting (EH) enabled unmanned aerial vehicles (UAVs) with non-orthogonal multiple access (NOMA) to enhance communication system performance within a cellular network. Addressing the limitations of existing analyses that often assume an infinite blocklength scenario, we explore EH-enabled UAV-NOMA systems within a cellular framework under

As the automotive industry advances towards greater automation, the proliferation of electronic control units (ECUs) has led to a substantial increase in the connectivity of in-vehicle networks with the external environment. However, the widely used Controller Area Network (CAN), which serves as the standard for in-vehicle networks, lacks robust security features, such as authentication or encrypted

The increasing number of connected and automated vehicles has led to a sharp increase in the demand for network access of moving vehicles. Although 5G networks support terminals with high mobility, the traffic load is too heavy to bear if all the vehicles have a large amount of data for transmission. Therefore, IEEE 802.11-based wireless network is a complementary offload solution to provide high-speed

Vehicular edge computing networks (VECNs) can provide a promising solution to support efficient task execution of vehicles. Consider the channel and access time variations caused by the high mobility of vehicles in a vehicular environment when designing task offloading strategies in VECNs. In this paper, we perform multi-path offloading for a task vehicle with serial tasks based on both dynamic communication

Nowadays, unmanned aerial vehicles (UAVs) organized in a flying ad hoc network (FANET) can successfully carry out complex missions. Due to the limitations of these networks, including the lack of infrastructure, wireless communication channels, dynamic topology, and unreliable communication between UAVs, cyberattacks, especially wormholes, weaken the performance of routing schemes. Therefore, maintaining

The Intelligent Transportation Systems (ITS) is a leading-edge, developing idea that seeks to revolutionize how people and things move inside and outside cities. Internet of Vehicles (IoV) forms a networked environment that joins infrastructure, pedestrians, fog, cloud, and vehicles to develop ITS. The IoV has the potential to improve transportation systems significantly, but as it is networked and

Vehicular Ad Hoc Networks (VANETs) offer a promising solution to bring drivers comfortable driving experiences and also improve road safety in intelligent transportation systems, but also faces many security issues. Collusive attack is one of the most challenging threats in VANETs because it violates the fundamental assumption made by VANET-based applications that all received information be correct

With the generation of massive traffic information in the smart transportation system, the traffic control center efficiently utilizes broadcast communication to send multiple messages to multiple vehicles. Besides, diversified privacy disclosure and security attack issues also emerged spontaneously. To achieve secure communication between the traffic control center and vehicles in the smart transportation

Analyzing vehicular ad hoc networks (VANETs) poses a considerable challenge due to their constantly changing network topology and scarce network resources. Furthermore, defining suitable routing metrics for adaptive algorithms is a particularly hard task since these adaptive decisions should be taken according to the current conditions of the VANET. The literature contains different approaches aimed

The automotive field is undergoing significant technological advances, which includes making the next generation of autonomous vehicles smarter, greener and safer through vehicular networks, which are often referred to as Vehicle-to-Everything (V2X) communications. Together with V2X, centralized maneuver management services for autonomous vehicles are increasingly gaining importance, as, thanks to

The continuous progression in cloud computing, edge computing, and associated technologies has notably hastened the progress of vehicle networking technology. This advancement is increasingly assuming a crucial role in enhancing driving safety, optimizing traffic management, and revolutionizing traffic control methodologies. The principal aim of Internet of Vehicles (IoV) technology is to establish

The Internet of Vehicles (IoV) for fog computing (FC) addresses issues such as traffic congestion, transportation efficiency, and privacy. Non-orthogonal multiple access (NOMA) is a popular technology that enhances spectral efficiency and increases the network's access capability. The synchronisation between NOMA and FC radio access networks extends the application of augmented or vehicular networking

Due to the progress of unmanned aerial vehicles (UAVs), this new technology is widely applied in military and civilian areas. Multi-UAV networks are often known as flying ad hoc networks (FANETs). Due to these applications, FANET must ensure communication stability and have high scalability. These goals are achieved by presenting clustering techniques in FANETs. However, the characteristics of these

In the Internet of Vehicles (IoV) domain, the collection of traffic data is executed by intelligent devices and stored within a cloud-assisted IoV system. However, ensuring confidentiality and authorized access to data are the main problems of data storage. To address these problems, this paper proposes an efficient heterogeneous online/offline certificateless signcryption with a proxy re-encryption

Vehicular Ad Hoc Networks (VANETs) provide various benefits and play a crucial role in improving efficiency and ensuring human safety across different applications. However, these advantages also give rise to security challenges and privacy concerns, necessitating a thorough examination of security attacks. Current key generation schemes, particularly those based on the Physical-Layer Model (PLM),

With the popularity of vehicular communication systems and mobile edge vehicle networking, intelligent transportation applications arise in Internet of Vehicles (IoVs), which are latency-sensitive, computation-intensive, and requiring sufficient computing and communication resources. To satisfy the requirements of these applications, computation offloading emerges as a new paradigm to utilize idle

This work explores distributed processing techniques, together with recent advances in multi-agent reinforcement learning (MARL) to implement a fully decentralized reward and decision-making scheme to efficiently allocate resources (spectrum and power). The method targets processes with strong dynamics and stringent requirements such as cellular vehicle-to-everything networks (C-V2X). In our approach

Intelligent Transportation System (ITS) is one of the newest technologies in the transportation sector that will give hope for better driving safety. Not only in terms of driving safety, but ITS will give also hope for driving comfort. Smart vehicles perchance better versatile to the street circumstances through trade data among vehicles. In case, they can maintain a strategic distance from activity

With the growing concern over range anxiety among electric vehicle (EV) owners due to limited battery capacity and sparse charging infrastructure, EV-to-EV (V2V) energy sharing emerges as a crucial solution to extend driving range. Leveraging the vehicular energy network (VEN) enabled by dynamic wireless power transfer (DWPT) technology, energy sharing among EVs in motion becomes feasible. However

Vehicular Ad-Hoc Networks (VANETs), a subset of Mobile Ad-Hoc Networks (MANETs), are wireless networks formed around moving vehicles, enabling communication between vehicles, roadside infrastructure, and servers. With the rise of autonomous and connected vehicles, security concerns surrounding VANETs have grown. VANETs still face challenges related to privacy with full-scale deployment due to a lack

Time-efficient route planning is a significant research area of Internet of Vehicular Things. Optimal route selection is important to reach the destination in minimal time. Further, energy efficiency is vital for route planning in a sustainable environment. To address these issues, this paper proposes a federated learning and genetic algorithm-based green edge computing framework for optimal route

Device-to-Device (D2D) communication when used in conjugation with Unmanned Aerial Vehicle (UAV) Femtocell and unlicensed spectrum can effectively tackle the ever-increasing mobile data demands. However, D2D communication raises security and privacy concerns among users due to the absence of a centralized entity such as a base station. Therefore, exploring social connections among users becomes imperative

Quantum-proof authentication is essential for vehicular communications as the threat of quantum computing attacks on traditional encryption methods grows. Several lattice-based authentication protocols have recently been developed to help with this issue, but they come with hefty storage and communication overheads. Most of them also fail to provide strong anonymity for vehicles and edge nodes and

To secure Vehicle-to-everything (V2X) communications, many Conditional Privacy-Preserving Authentication schemes (CPPA) use symmetric and asymmetric encryption during the authentication process. However, several existing schemes have some security limitations regarding VANET requirements. In many symmetric cryptography-based schemes, the participants are required to share the same keys which could

Vehicle-to-vehicle (V2V) communication is one of the promising communication applications designed to optimize traffic conditions and has played a crucial role in the improvement of intelligent transportation technologies. Since there is still some uncertainty regarding generalized models that provide a more accurate representation of propagation environments, the existing literature emphasizes the

The convergence of mobile edge computing (MEC) network with unmanned aerial vehicles (UAVs) presents an auspicious opportunity to revolutionize wireless communication and facilitate high-speed internet access in remote regions for mobile devices (MDs) as well as large scale artificial intelligence (AI) models. However, the substantial amount of data produced by the UAVs-assisted MEC network necessitates

Vehicular networks are vulnerable to Distributed Denial of Service (DDoS), an extension of a Denial of Service (DoS) attack. The existing solutions for DDoS detection in vehicular networks use various Machine Learning (ML) algorithms. However, these algorithms are applicable only in a single layer in a vehicular network environment and are incapable of detecting DDoS dynamics for different layers of

Since resource allocation of cellular networks is not dynamic, some cells may experience unplanned high traffic demands due to unexpected events. Unmanned aerial vehicles (UAV) can be used to provide the additional bandwidth required for data offloading.

The Internet of vehicles (IoV) is an essential part of modern intelligent transportation systems (ITS). In the ITS, intelligent connected vehicle can access a variety of latency-sensitive cloud services through the vulnerable wireless communication channel, which could lead to security and privacy issues. To prevent access by malicious nodes, a large number of authentication schemes have been proposed

The growing need for wide and ubiquitous accessibility to advanced Intelligent Transportation Systems (ITS) has led to the evolution of conventional Vehicle to Everything (V2X) paradigms into the Internet of Vehicles (IoVs). Next-generation IoVs establish seamless connections among humans, vehicles, Internet of Things (IoT) devices, and service platforms to enhance transit efficiency, road safety,

With the increasing prevalence of drones, guaranteeing their authentication and secure communication has become paramount in drone networks to mitigate unauthorized access and malicious attacks. Cross-domain authentication is crucial in the context of the Internet of Drones (IoD) for safely verifying and establishing trust between diverse drones and their respective control stations, which may belong