Vehicular Ad hoc NETworks are special case of ad hoc networks that, besides lacking infrastructure, communicating entities move with various accelerations. Accordingly, this impedes establishing reliable end-to-end communication paths and having efficient data transfer. Thus, VANETs have different network concerns and security challenges to get the availability of ubiquitous connectivity, secure communications, and reputation management systems which affect the trust in cooperation and negotiation between mobile networking entities. In this survey, we discuss the security features, challenges, and attacks of VANETs, and we classify the security attacks of VANETs due to the different network layers

Due to the fast development in communication technology and the emerging usage of Internet of Things (IoT) devices that produce a huge amount of data, the fifth generation (5G) mobile network is introduced to support this development. This mobile network can provide many advanced communication features in cellular phones. But unfortunately, this technology faces many challenges. One of its defective challenges is the management of a massive number of devices running different services, so Software Defined Network (SDN) is proposed as a key technology to overcome this drawback. SDN architecture provides higher flexibility, scalability, cost-effectiveness, and energy efficiency in 5G mobile networks. There are usually different architectures for the SDN control plane. We study some of these architectures, and we conciliate the usage of Logically Centralized-Physically Distributed (LC-PD) controller management architecture in 5G networks. This architecture enables providing higher throughput, and lower latency compared to other control plane architectures. In this paper, we focus on the demonstration that the LC-PD control plane architecture improves communication efficiency and the Quality of Services (QoS) of running internet services in the 5G mobile network. We use the Mininet-WIFI emulator in our simulation tests. Our conducted simulations show that employing the LC-PD control plane architecture in 5G networks enhances the QoS of Internet services compared to other SDN implementations.

Autonomous driving of higher automation levels asks for optimal execution of critical maneuvers in all environments. A crucial prerequisite for such optimal decision-making instances is accurate situation awareness of automated and connected vehicles. For this, vehicles rely on the sensory data captured from onboard sensors and information collected through V2X communication. The classical onboard sensors exhibit different capabilities and hence a heterogeneous set of sensors is required to create better situation awareness. Fusion of the sensory data from such a set of heterogeneous sensors poses critical challenges when it comes to creating an accurate environment context for effective decision-making in AVs. Hence this exclusive survey analyses the influence of mandatory factors like data pre-processing preferably data fusion along with situation awareness toward effective decision-making in the AVs. A wide range of recent and related articles are analyzed from various perceptive, to pick the major hiccups, which can be further addressed to focus on the goals of higher automation levels. A section of the solution sketch is provided that directs the readers to the potential research directions for achieving accurate contextual awareness. To the best of our knowledge, this survey is uniquely positioned for its scope, taxonomy, and future directions.

In a vehicular communications environment, the need for information sharing, entertainment, and multimedia will increase, leading to congestion of backhaul networks. The major challenge of this network is latency and resource limitations. Proactive caching can be obtained from local caches rather than from remote servers, which can avoid long delays resulting from limited backhaul capacity and resources. Therefore, proactive caching reduces latency and improves the quality of services. Determining which files should be cached in memory is a critical issue. The paper proposes various placement schemes for caching at the vehicle and mobile base station (MBS) layers. The optimal caching place represents better user demand and latency based on the demand and mobility model. Non-cooperative and cooperative vehicles with vehicle-to-vehicle communication (V2V) are included. In both models, the high data rate of visible light communication (VLC) in the vehicular networks tends to enhance the caching capability. We also illustrate a sub-optimal algorithm to solve optimization problems compared to the optimal brute force solver and the sub-optimal genetic algorithm. Numerical results show that proactive caching schemes have a significant gain in system performance. The analysis shows that VLC improves proactive caching performance when there are less than 25 vehicles. The joint proactive caching scheme works better as the number of vehicles increases. The V2V proactive caching is useful when vehicles per platoon are ≥10.

Security is a major challenge preventing wide deployment of the smart grid technology. Typically, the classical power grid is protected with a set of isolated security tools applied to individual grid components and layers ignoring their cross-layer interaction. Such an approach does not address the smart grid security requirements because usually intricate attacks are cross-layer exploiting multiple vulnerabilities at various grid layers and domains. We advance a conceptual layering model of the smart grid and a high-level overview of a security framework, termed CyNetPhy, towards enabling cross-layer security of the smart grid. CyNetPhy tightly integrates and coordinates between three interrelated, and highly cooperative real-time security systems crossing section various layers of the grid cyber and physical domains to simultaneously address the grid's operational and security requirements. In this article, we present in detail the physical security layer (PSL) in CyNetPhy. We describe an attack scenario raising the emerging hardware Trojan threat in process control systems (PCSes) and its novel PSL resolution leveraging the model predictive control principles. Initial simulation results illustrate the feasibility and effectiveness of the PSL.

Vehicular Cloud Computing (VCC) has become a significant research area recently, due to its potential advantages and applications, especially in the field of Intelligent Transportation Systems (ITS). However, the high mobility of vehicular environment poses crucial challenges to resources allocation and management in VCC, which makes its implementation more complex than conventional clouds. Many works have been introduced to address various issues and aspects of VCC, including resources management and Virtual Machine Migration in vehicular clouds. However, using mobility prediction in VCC has not been studied previously. In this paper, we introduce a novel solution to reduce the effect of resources mobility on the performance of vehicular cloud, using an efficient resources management scheme based on vehicles mobility prediction. This approach enables the vehicular cloud to take pre-planned procedures, based on the output of an Artificial Neural Network (ANN) mobility prediction model. The aim is to reduce the negative impact of sudden changes in vehicles locations on vehicular cloud performance. A simulation scenario is introduced to compare between the performance of our resources management scheme and other resources management approaches introduced in the literature. The simulation environment is based on Nagel-Shreckenberg cellular automata (CA) discrete model for traffic simulation. Simulation results show that our proposed approach has leveraged theperformance of vehicular cloud effectively without overusingavailable vehicular cloud resources.