Vehicular Ad Hoc Network Systems Research Articles

S2DN: Design of robust authentication protocol with session key establishment in multi-controller based software-defined VANETs

Advancements in technology and the adoption of innovative developments have significantly simplified our lives. One notable innovation in the networking domain is Software Defined Networking (SDN), which revolutionizes the network layer by enabling centralized network administration and re-programmability. SDN technology finds application in diverse fields such as Vehicular Ad-hoc Networks (VANETs), Wireless Sensor Networks (WSNs), Internet of Things (IoT) communications, and cloud-fog computing. The integration of SDN technology into VANET systems has notably improved network performance but has also raised security concerns. To tackle this issue, this paper focuses on devising an authentication mechanism to facilitate secure communication across various VANET levels by establishing a shared session key. Moreover, the research proposes a method to mitigate the challenge of single points of failure, a typically difficult issue to address. To ensure the security of all confidential information during protocol execution, simulations are conducted using the Scyther tool. Additionally, an informal security analysis is performed, demonstrating the robustness of the proposed protocol. The proposed protocol also performs outstanding in terms of performance results

Deploying a Low-Cost Wi-Fi-Based Vehicular Ad Hoc Network in a Shopping Mall Parking Lot: An Empirical Study

Vehicular ad hoc networks (VANETs) have the potential to reduce car accidents by facilitating connectivity and warning message exchange between vehicles, both on roads and in parking lots. This research endeavored to accomplish three primary goals: conducting a field measurement in the parking lot of a large shopping mall in Auckland, developing an OPNET-based simulation model to analyze and validate the system performance, and analyzing the compatibility between five selected radio propagation models (Free-space, Shadowing Path-loss, Egli, Hata, and COST231). These models were selected based on their popularity and relevance to our study. We found that the “Free Space” model outperforms in the scenario in which measurements were conducted from the Level-1 car park to the Roadside. The received signal strengths in the parking lot ranged from −45 dBm to −92 dBm. This research also examines the coverage distance for the successful transmission of warning messages, achieving up to 57 m, 17.5 m, 9.4 m, and 68 m at parking levels 1, 2, 3, and the roadside, respectively. Research findings reveal that a low-cost Wi-Fi-based VANET system can be utilized to prevent car accidents in parking lots. Finally, we provide guidelines for network planners to deploy Wi-Fi-based VANET systems in parking lots.

Millimeter-wave channel modeling in a VANETs using coding techniques.

The Vehicular ad-Hoc Network (VANET) is envisioned to ensure wireless transmission with ultra-high reliability. In the presence of fading and mobility of vehicles, error-free information between Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I) requires extensive investigation. The current literature lacks in designing an ultra-reliable comprehensive tractable model for VANET using millimeter wave. Ultra-reliable communication is needed to support autonomous vehicular communication. This article aims to provide a comprehensive tractable model for VANET over millimeter waves using Space-Time-Block-Coding (STBC) concatenated with Reed Solomon (RS) coding. The designed model provides the fastest way of designing and analyzing VANET networks on 60 GHz. By using the derived BER expressions and Reed Solomon coded doppler expression ultra-reliable vehicular networks can be build meeting the demands of massive growing volume of traffic. The performance of the model is compared with previous BER computational techniques and existing VANET communication systems, i.e., IEEE 802.11bd and 3rd generation partnership project vehicle to everything (3GPP V2X). The findings show that our proposed approach outperforms IEEE 802.11bd and the results are comparable with V2X NR. Packet Error Rate (PER), Packet Reception Ratio (PRR) and throughput are used as performance metrics. We have also evaluated the model on higher velocities of vehicles. Further, the simulation and numerical findings show that the proposed system surpass the existing BER results comprising of various modulation and coding techniques. The simulation results are verified by the numerical results there-by, showing the accuracy of our derived expressions.

DPB-MA: Low-Latency Message Authentication Scheme Based on Distributed Verification and Priority in Vehicular Ad Hoc Network

Vehicular ad hoc networks (VANETs) serve as crucial means to ensure safe transportation systems and enhance driving convenience. Ensuring authentication between vehicles and units is the most essential line of defense for VANETs systems. Various schemes of message authentication are put forward to realize safe communication in VANETs. However, these schemes mainly pay attention to privacy and security issues, and are not fit for high-density traffic environments where many messages should be verified by a roadside unit (RSU). At present, achieving the low-latency authentication under the security and privacy of messages remains a critical requirement and challenge. For addressing this problem, this study puts forward a novel low-latency message authentication scheme based on the distributed authentication and message priority (DPB-MA), which can minimize message verification latency through cooperation between the RSU and cooperative vehicles (CVs). In addition, a message priority strategy has been designed to ensure that urgent messages are preferentially verified. According to the security proof with tight reduction, the DPB-MA is existentially unforgeable against adaptive chosen message attack (EU-CMA) in the random oracle model (ROM). Furthermore, our DPB-MA achieves full message aggregation, which also greatly optimizes the communication overhead and authentication efficiency. Performance analysis indicates that our scheme works well in high-density traffic scenarios and is more suitable for securing emergency messages with ultra-low latency requirements.

A Review on Machine Learning Techniques Used in VANET and FANET Networks

The widespread use of the Internet and the increase in the number and variety of devices connected to the internet have led to the emergence of new methods in wireless communication. Dynamic and temporary Ad-Hoc networks, which do not require a fixed infrastructure as in traditional wireless network communication, are one of these new methods. The fact that Ad-Hoc networks do not need a fixed infrastructure has revealed a network structure with a lower cost and less configuration. Mobile Ad-Hoc networks play an important role, especially in the communication of nodes on the move. FANET (Flying Ad-Hoc Networks) networks, which are called flying ad hoc networks, are mobile Ad-Hoc networks used for communication of unmanned aerial vehicles (UAV), and VANET (Vehicular Ad-Hoc Networks) networks, which are called vehicular ad hoc networks, are mobile Ad-Hoc networks used for communication of road vehicles. The development and dissemination of these networks make a significant contribution to the development of autonomous vehicles and UAVs. The increase in the use of FANET and VANET networks, which are specialized subnets of mobile Ad-Hoc networks, and the increase in the number of nodes in these networks have caused problems related to security, efficiency, and sustainability in these networks. Machine learning methods, one of today' s effective and common approaches, are one of the ways that are frequently used in solving the problems specified in FANET and VANET networks. The rapid topology change, which is one of the most important features of these networks, makes it difficult to provide traffic management, trust management, routing, and data transmission. In this direction, machine learning approaches play an active role. In this study, it is presented by examining which machine learning techniques are used in the literature to perform important tasks such as traffic management, trust management, routing, and data transfer. Thus, it is aimed for those who will work in these fields to acquire information about machine learning approaches that can be used. Since the FANET network type is a new approach, it has been observed that there are few studies using machine learning. In VANET systems, studies using machine learning methods are especially intense in 2021. This study was carried out to give the reader an idea about which machine learning methods can be used in which problems in FANET and VANET networks.

Secure authentication and privacy-preserving to improve video streaming vehicle ad-hoc network

In vehicular ad hoc networks (VANET), the privacy of vehicle data symbolizes a big challenge towards malicious attacks. On the other side, vehicles in VANET can play a staple role in monitoring the environment by sensing the surrounding environment, compute the sensing information, and transfer the results if needed to the authorized party. Most of the modern VANETs systems encrypt the information to prevent hacking it but mostly neglect the decryption that occurred when data need to re-processed. In this paper, we try to cover this weak point by using fully homomorphic encryption (FHE) because of its specifications. The proposed work focus on twofold: first, create secure authentication and permission management system. While the second is to preserve the privacy of vehicle data that transferred among VANET infrastructure. This scheme also deals with metric security features, such as data privacy, data integrity, and key management. In the experimental results, there is good advance in the fields of interest comparing with the related works.

Blockchain-based vehicular ad-hoc networks: A comprehensive survey

Vehicular ad-hoc networks (VANETs) are increasingly commonplace, partly due to the popularity of electric vehicles and the digitalization of cities. Data collected and shared in VANETs include traffic-related information, such as those relating to real-time traffic situations and road works. In recent times, there has been a trend of moving away from a centralized approach to a decentralized approach, for example, using Blockchain to facilitate secure data sharing and traceability of critical information. Hence, in this paper, we comprehensively survey the existing literature on blockchain-based VANET systems, focusing on the application of different blockchain technologies in different contexts, as well as the associated challenges and research opportunities.

Simulation of IoT-based Vehicular Ad Hoc Networks (VANETs) for Smart Traffic Management Systems

Nowadays, traffic congestion and increasing road accidents have become a major concern for both developed and developing countries. To overcome this challenge, an internet of things- (IoT-) based Vehicular Ad Hoc Network (VANET) system is proposed in which vehicles interact with other vehicles and infrastructure. These self-organized ad hoc vehicle networks not only boost traffic safety but also enhances the efficiency of traffic management systems. The VANET systems are beneficial in busy locations, where improved data dissemination protocols are used to categorize a vehicle’s transmission. However, the performance of these VANETs is also hampered by network splits and insufficient connections. Under these situations, the proposed simulation model reduces broadcast storms by minimizing redundancies, which is equally beneficial for both rural and urban settings. The suggested Next Forwarder Vehicle (NFV) protocol is based on three factors: position, distance, and orientation. Moreover, the DDP4V technique is used to analyse each of these features. Results indicate that DDP4V is compatible with 96% of all traffic scenarios and simulation durations. It can transport data packets 60% faster due to its broadcast suppression capabilities. Also, in comparison to AID and DBRS, DDP4V has fewer dispersed packets, which results into reduced retransmissions. For 200 automobiles/km2, all these techniques accomplish 35–40% of the needed cars. However, the coverage also faces some restrictions since data packets only reach vehicles on the same side as the originating vehicle. Similarly, DDP4V delivers 90% coverage for 400 vehicles/km2, which is 30% greater than prior techniques. It is observed that the proposed protocol reduces broadcast storms by employing a waggon wheel to choose the next forwarding vehicle. In high-traffic areas, it outperforms standard techniques. Similarly, it employs a patchwork of vehicles outside of the impacted region to convey data. The industrial IoT-based VANETs provide an effective tool to monitor and control traffic besides reducing the number of traffic accidents.

QoS Aware and Fault Tolerance Based Software-Defined Vehicular Networks Using Cloud-Fog Computing.

Software-defined network (SDN) and vehicular ad-hoc network (VANET) combined provided a software-defined vehicular network (SDVN). To increase the quality of service (QoS) of vehicle communication and to make the overall process efficient, researchers are working on VANET communication systems. Current research work has made many strides, but due to the following limitations, it needs further investigation and research: Cloud computing is used for messages/tasks execution instead of fog computing, which increases response time. Furthermore, a fault tolerance mechanism is used to reduce the tasks/messages failure ratio. We proposed QoS aware and fault tolerance-based software-defined V vehicular networks using Cloud-fog computing (QAFT-SDVN) to address the above issues. We provided heuristic algorithms to solve the above limitations. The proposed model gets vehicle messages through SDN nodes which are placed on fog nodes. SDN controllers receive messages from nearby SDN units and prioritize the messages in two different ways. One is the message nature way, while the other one is deadline and size way of messages prioritization. SDN controller categorized in safety and non-safety messages and forward to the destination. After sending messages to their destination, we check their acknowledgment; if the destination receives the messages, then no action is taken; otherwise, we use a fault tolerance mechanism. We send the messages again. The proposed model is implemented in CloudSIm and iFogSim, and compared with the latest models. The results show that our proposed model decreased response time by 50% of the safety and non-safety messages by using fog nodes for the SDN controller. Furthermore, we reduced the execution time of the safety and non-safety messages by up to 4%. Similarly, compared with the latest model, we reduced the task failure ratio by 20%, 15%, 23.3%, and 22.5%.

Dynamic Vehicular Clustering Enhancing Video on Demand Services Over Vehicular Ad-hoc Networks

Nowadays, video streaming applications are becoming one of the tendencies driving vehicular network users. In this work, considering the unpredictable vehicle density, the unexpected acceleration or deceleration of the different vehicles included in the vehicular traffic load, and the limited radio range of the employed communication scheme, we introduce the “Dynamic Vehicular Clustering” (DVC) algorithm as a new scheme for video streaming systems over vehicular ad-hoc networks (VANET). The proposed algorithm takes advantage of the small cells concept and the introduction of wireless backhauls, inspired by the different features and the performance of the Long Term Evolution (LTE)-Advanced network. Vehicles are clustered together to form dynamically ad-hoc sub-networks included in the vehicular network. The goal of our clustering algorithm is to take into account several characteristics, such as the vehicle's position and acceleration to reduce latency and packet loss. Therefore, each cluster is counted as a small cell containing vehicular nodes and an access point that is elected regarding some particular specifications. Based on the exceptional features of the LTE-Advanced network (small cells and wireless backhauls) the DVC algorithm is a promising scheme for video streaming services over VANET systems. Experiments were carried out with a virtual topology of the VANET network created with four clusters to implement the DVC algorithm. The results were compared with other algorithms such as Virtual Trust-ability Data transmission (VTD), Named Data Networking (NDN), and Socially Aware Security Message Forwarding (SASMF). Our algorithm can effectively improve the transmission rate of data packets at the expense of a slight increase in end-to-end delay and control overhead.

Deep network approach with stacked sparse autoencoders in detection of DDoS attacks on SDN‐based VANET

Software-defined network (SDN)-based vehicular ad hoc network (VANET) is an outstanding technology for smart transportation as it increases traffic safety, efficiency, comfort, and manageability. However, despite all its benefits and good performance, SDN-based VANET is vulnerable to attack threats such as distributed denial of service (DDoS). When SDN-based VANET systems are exposed to DDoS attacks, this may affect traffic safety, causing traffic accidents and deaths. Therefore, the relevant security threats need to be addressed before integrating the SDN-based VANETs into smart transportation systems. In this study, the stacked sparse autoencoder (SSAE) + Softmax classifier deep network model is proposed to detect DDoS attacks targeting SDN-based VANETs. The features in the dataset obtained from the SDN-based VANET were reduced dimensionally utilising SSAE, and the most significant features were obtained. Then, these features were used as input into the Softmax classifier. According to the experimental results, the best accuracy scores were calculated as 96.9% using the four-layer SSAE + Softmax classifier deep network model proposed. When compared, the results demonstrate the SSAE + Softmax classifier deep network model proposed can obtain better results in the classification of DDoS attacks and is more successful than the other machine learning classifiers.

Machine learning models and techniques for VANET based traffic management: Implementation issues and challenges

Low latency in communication among the vehicles and RSUs, smooth traffic flow, and road safety are the major concerns of the Intelligent Transportation Systems. Vehicular Ad hoc Network (VANET) has gained attention from various research communities for such a matters. These systems need constant monitoring for proper functioning, opening the doors to apply Machine Learning algorithms on enormous data generated from different applications in VANET (for example, crowdsourcing, pollution control, environment monitoring, etc.). Machine Learning is an approach where the system automatically learns and improves itself based on previously processed data. These algorithms provide efficient supervised and unsupervised learning of these collected data, which effectively implements VANET’s objective. We highlighted the safety, communication, and traffic-related issues in VANET systems and their implementation in-feasibility and explored how machine learning algorithms can overcome these issues. Finally, we discussed future direction and challenges, along with a case study depicting a VANET based scenario.

A Proactive Reliable Mechanism-Based Vehicular Fog Computing Network

As vehicles are becoming more and more intelligent, mobile data traffic in vehicular ad hoc network (VANET) has been increasing dramatically. This makes the communication capacity of VANET systems and the computing resources of vehicles insufficient. In the meantime, location-aware large-scale distributed services with very low latency and high reliability are demanded by most of the novel functions, such as accident alarming, and congestion warning, in the intelligent transportation system. To meet these claimed characteristics of VANET, we first present a novel architecture that integrates vehicular fog computing and vehicle-to-vehicle (V2V) communication technologies. Lower latency and higher quality services can be supplied to vehicles by nearby fog servers, which are virtualized from vehicles that locate close enough and communicate using the V2V link. However, like all collaborative systems, computing reliability is vital to collaborative VANET. In this article, we design a novel energy-efficient proactive replication mechanism. Follower vehicles calculate with a lazy rate act as backups of host vehicles to ensure the reliability of the system. Considering the time sensitivity of computing requirements in VANET, the upper bound on the total number of failures is proposed through theoretical analysis. Then, the lower bound on the lazy calculating rate of followers is derived by balancing the tradeoffs between delay and energy. A fast algorithm for searching this lower bound based on the discrete Newton method is also proposed. Results of numerical experiments show that our new mechanism is effective in energy saving and reliability enhancing.

HOMOMORPHIC AGGREGATE SIGNATURE SCHEME WITH OUTSOURCING ALGORITHM BASED PRIVACY PRESERVING IN VANETS

One of the important paradigms of recent technological development has known to be Vehicular Ad-hoc Networks (VANETs) due to its current intelligent transportation network. Moreover, leakage of communication information or sensitive data in VANETs can leads to vulnerable attacks that may affect many properties and lives. For this reason, VANET systems need to have high-level security aspects. In addition, devices with less computing resources expected for fast computation power. Several researchers have analysed various privacy preserving models for VANETs to protect from different attacks, which is not enough to prevent from new attackers. In this research, a Homomorphic Aggregate Signature (HAS) scheme proposed for achieving unforgeable message attacks without having random oracle and new outsourcing algorithm is designed efficiently for exponential operations to reduce the computational cost in which matrices conjugate operation based on homomorphic mapping is used for achieving the security of both base and exponent numbers. In addition, a protocol based on privacy preserving is constructed for VANETs by using the proposed HAS scheme and outsourcing computing, in which the authentication is processed by presenting a proxy re-signature scheme. In this proposed protocol, RSU will act as an agent when TA authorizes it and OBU’s signatures are converted to TA’s signature by using RSU. Real-identity of OBU is traced by TA using its secret key when an unknown/malicious message is detected then the proposed protocol will provide traceability, privacy, and anonymity. Furthermore, pairing and exponential operations are not needed by the proposed scheme as ` complexity of calculations is reduced significantly for VANET system.

A Blockchain-SDN-Enabled Internet of Vehicles Environment for Fog Computing and 5G Networks

The goal of intelligent transport systems (ITSs) is to enhance the network performance of vehicular ad hoc networks (VANETs). Even though it presents new opportunities to the Internet of Vehicles (IoV) environment, there are some security concerns including the need to establish trust among the connected peers. The fifth-generation (5G) communication system, which provides reliable and low-latency communication services, is seen as the technology to cater for the challenges in VANETs. The incorporation of software-defined networks (SDNs) also ensures an effective network management. However, there should be monitoring and reporting services provided in the IoV. Blockchain, which has decentralization, transparency, and immutability as some of its properties, is designed to ensure trust in networking platforms. In that regard, this article analyzes the combination of blockchain and SDN for the effective operation of the VANET systems in 5G and fog computing paradigms. With managerial responsibilities shared between the blockchain and the SDN, it helps to relieve the pressure off the controller due to the ubiquitous processing that occurs. A trust-based model that curbs malicious activities in the network is also presented. The simulation results substantially guarantee an efficient network performance, while also ensuring that there is trust among the entities.

SAFE-MAC: Speed Aware Fairness Enabled MAC Protocol for Vehicular Ad-hoc Networks.

Highly dynamic geographical topology, two-direction mobility, and varying traffic density can lead to fairness issues in Vehicular Ad-hoc Networks (VANETs). The Medium Access Control (MAC) protocol plays a vital role in sharing the common wireless channel efficiently between vehicles in a VANET system. However, ensuring fairness between vehicles can be a challenge in designing MAC protocols for VANET systems. The existing protocol, IEEE 802.11 DCF, ensures that the packet transmission rate for a particular vehicle is directly proportional to the amount of time a vehicle spends within a service area, but it does not guarantee that faster vehicles will be able to send the minimum number of packets. Other existing MAC protocols based on IEEE 802.11 are able to provide a minimum amount of data transmission regardless of velocity, but are unable to provide an amount of data transmission that is more proportionate to the time a vehicle spends in the service area. To address the above limitations, we propose a Speed Aware Fairness Enabled MAC (SAFE-MAC) protocol that calculates the residence time of a vehicle in a service area by using mobility metrics such as position, direction, and speed to synthesize the transmission probability of each individual vehicle with respect to its residence time. This is achieved by dynamically altering the values of parameters such as minimum contention window, maximum backoff stage, and retransmission limit in the MAC protocol. We then develop an analytical model to compare the performance of our proposed protocol with contemporary MAC protocols. Numerical analysis results show that our proposed protocol significantly improves fairness among the speed-varying vehicles in VANET.

An Efficient and Secure Key Agreement Protocol for Sharing Emergency Events in VANET Systems

With the recent rapid increase in the number of motor vehicles on roads, traffic accidents have increased, and emergency reporting processes have become essential. In this paper, a key agreement protocol for a real-time traffic sharing system is proposed for Vehicular Ad-Hoc Networks (VANETs), in which a broadcast center authenticates the legitimacy of a user when they report an emergency and issues a certificate of emergency to other users. This study uses a digital signatures mechanism, key agreement and authentication scheme to satisfy the security requirements for a VANET. Burrows-Abadi-Needham logic (BAN logic) is applied to prove that the proposed scheme achieves secure authentication. The proposed protocol ensures the privacy of the communication between fleets and provides a mechanism for immediate emergency reporting. The experiment results show that the proposed scheme is feasible and meets security requirements.

Trajectory tracking and recovery attacks in VANET systems

SummaryInvestigating the mechanisms of various attacks in vehicular ad hoc networks (VANETs) provides fundamental basis to develop safeguard techniques for network security issues. As they develops, attacking strategies are also needed to be established for people to learn how to defend. Previous works failed to consider multiple victims recovery and minimum road side units (RSUs) deployment issues. In this paper, we approach the attacking strategy from an adversarial point of view and develop a trajectory tracking and recovering attack based on matrix completion (TTRA). By randomly sampling locations of vehicles, TTRA is capable of recovering locations of any user with tolerable deviation. After that, the problem of how to minimize the number of RSUs while tracking all vehicles in the whole region is also considered by converting this problem into set covering problem. A heuristic algorithm based on hierarchical clustering is proposed accordingly. To the best of our knowledge, this is the first attempt of recovering mobile users' trajectories by applying these novel techniques. Finally, simulation analysis is used to show the performance of the proposed scheme. Simulation results demonstrate the merits of the scheme in terms of tracking results, location error, and influences of sampling ratio, among others.

Services and Security Threats in SDN Based VANETs: A Survey

As the number of vehicles is increasing, the number of road side accidents is also increasing rapidly. The majority of these accidents is caused by the negligence of the driver. For intelligent transportation services, new protocols and architecture are continuously being developed by researchers around the globe. Thus to ensure the safety of drivers many countries are now adopting and investing a lot on vehicular ad hoc network (VANET). On the other perspective, there are many issues related to this field that must be resolved before VANET technology is practically adopted. In the case of no or low-security, several attacks can occur that may affect the efficiency and the reliability of the system. To make VANET systems more efficient software defined networking (SDN) technology is introduced in it. This technique was shortly named as SDN-based VANET. SDN-based VANET system helps us to get rid of the restriction and the challenges that are present in the simple VANET systems. It helps us to decrease the overall load on the network by managing the overall network through a single remote controller. In this survey paper, we will elaborate the concept of SDN-based VANET, its working, applications, services, security threats, and benefits over the previous techniques.

A New Approach for Improvement Security against DoS Attacks in Vehicular Ad-hoc Network

Vehicular Ad-Hoc Networks (VANET) are a proper subset of mobile wireless networks, where nodes are revulsive, the vehicles are armed with special electronic devices on the motherboard OBU (On Board Unit) which enables them to trasmit and receive messages from other vehicles in the VANET. Furthermore the communication between the vehicles, the VANET interface is donated by the contact points with road infrastructure. VANET is a subgroup of MANETs. Unlike the MANETs nodes, VANET nodes are moving very fast. Impound a permanent route for the dissemination of emergency messages and alerts from a danger zone is a very challenging task. Therefore, routing plays a significant duty in VANETs. decreasing network overhead, avoiding network congestion, increasing traffic congestion and packet delivery ratio are the most important issues associated with routing in VANETs. In addition, VANET network is subject to various security attacks. In base VANET systems, an algorithm is used to dicover attacks at the time of confirmation in which overhead delay occurs. This paper proposes (P-Secure) approach which is used for the detection of DoS attacks before the confirmation time. This reduces the overhead delays for processing and increasing the security in VANETs. Simulation results show that the P-Secure approach, is more efficient than OBUmodelVaNET approach in terms of PDR, e2e_delay, throughput and drop packet rate.