The increased use of smart Electric Vehicles (EVs) and Plug-in Electric Vehicles (PEV) opened a new area of research and development. The number of EV charging sites has considerably increased in residential as well as in public areas. Within these EV charging sites, various entities need to communicate in a secure and efficient way. The Open Charge Point Protocol (OCPP) offers a way to coordinate this communication and is already being used in many implementations. However, only the latest OCPP 2.0 version of the protocol includes certain security features. In this article, we present the entities that take part in an OCPP-based smart charging scenario, we identify security issues and threats and present solutions that have been proposed by scholars. We identify open security issues for OCPP and propose future research directions for the security enhancement of the protocol.

Heterogenous cellular networks (HCN) introduce small cells within the transmission range of a macrocell. For the efficient operation of HCNs it is essential that the high-power macrocell shuts off its transmissions for an appropriate amount of time in order for the low-power small cells to transmit. This is a mechanism that allows time-domain resource partitioning (TDRP) and is critical to be optimized for maximizing the throughput of the complete HCN. In this paper, we investigate video communication in HCNs when TDRP is employed. After defining a detailed system model for video streaming in such an HCN, we consider the problem of maximizing the experienced video quality at all the users, by jointly optimizing the TDRP for the HCN, the rate allocated to each specific user, and the selected video quality transmitted to a user. The NP-hard problem is solved with a primal-dual approximation algorithm that decomposes the problem into simpler subproblems, making them amenable to fast well-known solution algorithms. Consequently , the calculated solution can be enforced in the time scale of real-life video streaming sessions. This last observation motivates the enhancement of the proposed framework to support video delivery with dynamic adaptive streaming over HTTP (DASH). Our extensive simulation results demonstrate clearly the need for our holistic approach for improving the video quality and playback performance of the video streaming users in HCNs.

Channel coding is a fundamental procedure in wireless telecommunication systems and has a strong impact on the data transmission quality. This effect becomes more important when the transmission must be characterised by low latency and low bit error rate, as in the case of vehicle-to-everything (V2X) services. Thus, V2X services must use powerful and efficient coding schemes. In this paper, we thoroughly examine the performance of the most important channel coding schemes in V2X services. More specifically, the impact of use of 4th-Generation Long-Term Evolution (4G-LTE) turbo codes, 5th-Generation New Radio (5G-NR) polar codes and low-density parity-check codes (LDPC) in V2X communication systems is researched. For this purpose, we employ stochastic propagation models that simulate the cases of line of sight (LOS), non-line of sight (NLOS) and line of sight with vehicle blockage (NLOSv) communication. Different communication scenarios are investigated in urban and highway environments using the 3rd-Generation Partnership Project (3GPP) parameters for the stochastic models. Based on these propagation models, we investigate the performance of the communication channels in terms of bit error rate (BER) and frame error rate (FER) performance for different levels of signal to noise ratio (SNR) for all the aforementioned coding schemes and three small V2X-compatible data frames. Our analysis shows that turbo-based coding schemes have superior BER and FER performance than 5G coding schemes for the vast majority of the considered simulation scenarios. This fact, combined with the low-complexity requirements of turbo schemes for small data frames, makes them more suitable for small-frame 5G V2X services.

Jamming is a terrifying attack that could harm 802.11p-based vehicular communications by occupying the communication channels by overwhelming the network with jamming packets, especially for self-driving cars, as it is essential to send/receive messages without any interruptions to control the vehicles remotely. In wireless vehicular ad hoc networks (VANET), the attacker’s mission is more accessible due to the network’s open nature, way of communication, and lack of security measures. Most of the existing studies have focused on jamming detection approaches. However, few of them have addressed the jammer localization challenge. Moreover, even in these limited studies, the solutions’ assumptions, the proposed countermeasures, and their complexity were also missing. Therefore, this paper introduces a new approach to detecting, localizing, and avoiding jamming attacks in VANETs with high efficiency in terms of accuracy, implementation and complexity. The proposed approach uses the signal strength of the jammer for estimating only the distance between jammer and receiver, while then a less complex algorithm is proposed for localizing the jammer and then redirecting the vehicles away from the roads the attacker is using. This approach was simulated using real-life maps and specialized network environments. Additionally, the performance of the new approach was evaluated using different metrics. These evaluation metrics include (1) the estimated position of the jammer, (2) the handling of the jammer by announcing its location to normal vehicles (3) the avoidance of the jammed routes by increasing their weight, which forces the cars to reroute and evade the jamming area. The high localization accuracy, measured by the Euclidean distance, and the successful communication of the attacker’s position and its avoidance have highly increased the packet delivery ratio (PDR) and the signal-to-interference-plus-noise ratio (SINR). This was noticed significantly before and after avoiding the jamming area when for example, the PDR increased from 0% to 100% before and after bypassing the jammer’s routes.

Vehicular Ad Hoc Networks (VANETs) aim at enhancing road safety and providing a comfortable driving environment by delivering early warning and infotainment messages to the drivers. Jamming attacks, however, pose a significant threat to their performance. In this paper, we propose a novel Relative Speed Estimation Algorithm (RSEA) of a moving vehicle that approaches a transmitter ()-receiver () pair that interferes with their radio frequency (RF) communication by conducting a denial of service (DoS) attack. Our scheme is completely passive and uses a pilot-based received signal without hardware or computational cost to, firstly, estimate the combined channel between the transmitter-receiver and jammer-receiver and, secondly, to estimate the jamming signal and the relative speed between the jammer-receiver using the RF Doppler shift. Moreover, the relative speed metric exploits the angle of projection (AOP) of the speed vector of the jammer in the axis of its motion in order to form a two-dimensional representation of the geographical area. Our approach can effectively be applied for any form of the jamming signal and is proven to have quite accurate performance, with a mean absolute error (MAE) value of approximately compared to the optimal zero MAE value under different jamming attack scenarios.

Vehicle-to-everything (V2X) communications is an emerging branch of wireless communications and has recently gained a lot of interest not only from academia but also from the automotive and telecommunications industry. An important feature of V2X telecommunication systems is that the communication quality varies quickly in time due to the high mobility of the transceivers and due to the rapid change in the fading characteristics of the communication medium. For this reason, it is vital to maintain tolerable quality of service (QoS) in a V2X communication environment, in terms of communication reliability, power, end-to-end latency, data rate, communication range, throughput and vehicle density. A significant impact on the quality parameters of the system has been the coding scheme used by the V2X telecommunication system. For this purpose, we examine the effect that popular coding schemes have on the QoS of a V2X communication system. More specifically, the impact of fourth-generation long-term evolution (4G-LTE) turbo codes, fifth-generation new radio (5G-NR) polar codes and 5G-NR low-density parity-check codes (LDPC) on the QoS parameters of a V2X communication system is researched. Το this end, we employ stochastic V2X propagation models that simulate every possible V2X channel state and traffic environment, based on the third-generation partnership project (3GPP) Release 16 specifications. These propagation models form the basis of our study, since through them, at a first level, we analyze the frame error rate (FER) performance for different levels of signal-to-noise ratios (SNRs) for all the aforementioned coding schemes and 128-bit V2X-compatible data frames, and, at a second level, we investigate the impact of these propagation models and coding schemes on the V2X QoS parameters. Our analysis shows that turbo-based coding schemes satisfy all the QoS parameters and achieve overall communication quality comparable to polar and better than LDPC, making them suitable for small-frame 5G V2X services.