Development of Software Defined Networking (SDN) based Vehicular Ad Hoc Networks (VANETs) is one of the key enablers of 5G technology. VANETs enable different types of services through communication ...between vehicles and road side units. Intelligent Transportation System (ITS) introduced this emerging technology to provide travelers comfort, safety, and infotainment services with improved traffic efficiency. Traditional VANET is not sufficient to handle dynamic and large scale networks with their fixed and embedded policies, and complex architecture. Open Network Foundation (ONF) is promoting the adoption of SDN through open standards' development by facilitating logical and centralized control of the entire network. SDN enables VANET to be a flexible and programmable network with the advent of new services and features. A centralized controller in the control plane controls the overall network functionalities and forwarding of data packets through the forwarding devices in the data plane. SDN enhances the efficiency of VANET and provides security benefits to VANET. But, it causes new security problems also with the integration of new technologies and architectural components in the network. This article provides a comprehensive review of VANET, SDN, and SDN based VANETs based on their architectural and implementation details. Then it explains the effect of SDN on the security of VANET when it is integrated with traditional VANET. This paper encompasses a comprehensive review of proposed approaches providing security solutions for SDN based VANETs and outlines emerging research issues as future directions. To the best of our knowledge, this is the first article presenting the comprehensive review of security aspects of SDN based VANET considering architectural and security services on different layers of a network.
As the number of vehicles grows, traffic efficiency is becoming a worldwide problem. Intelligent transportation system aims to improve the traffic efficiency, where intelligent traffic light control ...is an important component. Existing intelligent traffic light control systems face some challenges, e.g., avoiding heavy roadside sensors, resisting malicious vehicles and avoiding single-point failure. To cope with those challenges, we propose two secure intelligent traffic light control schemes using fog computing whose security are based on the hardness of the computational Diffie–Hellman puzzle and the hash collision puzzle respectively. The two schemes assume the traffic lights are fog devices. The first scheme is a simple extension of a recent scheme for defending denial-of-service attacks. We show this simple extension is not efficient when the vehicle density is high. The second scheme is much more efficient and is fog device friendly. Even the vehicle density is high, the traffic light may verify the validity of the vehicles efficiently.
•Our schemes may resist the attacks from malicious vehicles.•Our schemes can avoid the problem of single-point failure.•Our improved scheme is fog device friendly.
Vehicular ad hoc network (VANET) is expected to improve our driving experience through enhanced safety, security, robustness, and infotainment. Nevertheless, despite considerable amount of research, ...VANET did not make it, at least not on a full scale, to the deployment stage because of many issues including security and privacy. However it is speculated that in the future high-end vehicles, on-board computation, communication, and storage resources will be under-utilized. Therefore, recently a new paradigm shift from conventional VANET to vehicular cloud computing was envisioned. This paradigm shift was realized through merging VANET with revolutionary cloud computing. Clearly cloud computing is one of today’s tempting technology areas due, at least partially, to its virtualization and cost-effectiveness. However, to date the potential architectural framework for VANET-based cloud computing has not been defined so far. To fill this gap, in this paper, first we put forth the taxonomy of VANET based cloud computing and then define a communication paradigm stack for VANET clouds. Additionally we divide VANET clouds into three architectural frameworks namely vehicular clouds (VC), vehicles using clouds (VuC), and hybrid vehicular clouds (HVC). Each proposed framework provides particular set of services depending upon the underlying communication paradigm. To understand our proposed framework well, we also propose a novel use-case service of the VANET-based cloud namely traffic information dissemination through clouds. In the proposed scheme, vehicles moving on the road are provided with fine-grained traffic information by the cloud as a result of their cooperation with the cloud infrastructure. Vehicles share their frequent mobility dynamics with the cloud and cloud in turn provides them with long range traffic information based on their current and near-future locations. Our simulation results show that the traffic information dissemination through cloud is feasible and the vehicles receive above 83 % of the traffic information from clouds through gateways in worst-case scenarios (i.e. extensive dense traffic) and above 90 % traffic information in average case scenarios. Finally we also outline the unique security and privacy issues and research challenges in VANET clouds.
The Vehicular Ad-hoc Network (VANET) represents a new future for dynamic information dissemination between societies. VANET has a wide range of applications in a variety of aspects, including ...Intelligent Transportation Systems (ITS). VANET has some characteristics, like highly dynamic topology and intermittent connections. These characteristics lead to untrustworthy information transmission in VANET. Vehicle clustering is an efficient approach to improve the scalability of the network and connection reliability. The performance of the clustering is also affected by VANET characteristics. This article provides a comprehensive description of VANET clustering algorithms. The most notable clustering algorithms introduced between 1999 and 2021 are reviewed. A complete survey on clustering in VANETs is provided based upon the clustering process. The clustering process in most algorithms is explored in the aspects of CH selection metrics, cluster formation, and cluster maintenance. The clustering techniques based on some parameters like stability, convergence, overhead, and latency are compared. Some of the most common problems, as well as the approaches employed to solve them, are also discussed. Also, the performance parameters which evaluate the clustering approaches are summarized.
In the Vehicular Ad-hoc NETworks (VANET), the collection and dissemination of life-threatening traffic event information by vehicles are of utmost importance. However, traditional VANETs face several ...security issues. We propose a new type of blockchain to resolve critical message dissemination issues in the VANET. We create a local blockchain for real-world event message exchange among vehicles within the boundary of a country, which is a new type of blockchain suitable for the VANET. We present a public blockchain that stores the node trustworthiness and message trustworthiness in a distributed ledger that is appropriate for secure message dissemination.
Abstract
Routing attacks will have distressing effects over the network and bequest a significant challenge once planning strong security mechanisms for vehicular communication. In this paper, we ...examine the effect and malicious activities of a number of the foremost common attacks and also mention some security schemes against some major attacks in VANET. The attacker’s aim is only to modify the actual route or provides the false data about the route to the sender and also some attackers are only flooding unwanted packets to consume resources in available network. Various routing approaches are also mentioned in the paper because the routing of data is very important to deliver the traffic information to leading vehicles. It’s advised that a number of the ways that to approach this made field of analysis issues in VANET might be to fastidiously design new secure routing protocols in which attacks are often rendered meaningless and because of the inherent constraints found in the network, there’s a desire for light-weight and sturdy security mechanisms.
Vehicular Adhoc Networks (VANET) facilitate inter‐vehicle communication using their dedicated connection infrastructure. Numerous advantages and applications exist associated with this technology, ...with road safety particularly noteworthy. Ensuring the transportation and security of information is crucial in the majority of networks, similar to other contexts. The security of VANETs poses a significant challenge due to the presence of various types of attacks that threaten the communication infrastructure of mobile vehicles. This research paper introduces a new security scheme known as the Soft Computing‐based Secure Protocol for VANET Environment (SC‐SPVE) method, which aims to tackle security challenges. The SC‐SPVE technique integrates an adaptive neuro‐fuzzy inference system and particle swarm optimisation to identify different attacks in VANETs efficiently. The proposed SC‐SPVE method yielded the following average outcomes: a throughput of 148.71 kilobits per second, a delay of 23.60 ms, a packet delivery ratio of 95.62%, a precision of 92.80%, an accuracy of 99.55%, a sensitivity of 98.25%, a specificity of 99.65%, and a detection time of 6.76 ms using the Network Simulator NS2.
This research paper introduces a new security scheme known as the Soft Computing‐based Secure Protocol for VANET Environment (SC‐SPVE) method, which aims to tackle security challenges. The SC‐SPVE technique integrates an adaptive neuro‐fuzzy inference system and particle swarm optimization to identify different attacks in VANETs efficiently.
This paper analyzes the information delivery delay for the purpose of roadside unit (RSU) deployment in a vehicular ad hoc network (VANET) with intermittent connectivity. A mathematical model is ...developed to describe the relationship between the average delay for delivering road condition information and the deployment distance between two neighbor RSUs. The derived mathematical model considers a sparse highway scenario where two neighbor RSUs are deployed at a distance without a direct connection, and vehicles are sparsely distributed on the road with road condition information randomly generated between the two neighbor RSUs. Moreover, the model takes into account the vehicle speed, the vehicle density, the likelihood of an incident, and the deployment distance between two neighbor RSUs. The correctness and accuracy of the derived mathematical model is verified, and the impacts of different parameters on the average information delivery delay are investigated through simulation results. Given an information delivery delay constraint for time-critical applications, this model can be used to estimate the maximum deployment distance allowed between two neighbor RSUs, which can provide a reference for the deployment of RSUs in such scenarios.
Vehicular networks have become a visible reality enabling information sharing between vehicles to enhance driving safety and provide value-added services to drivers and passengers. However, false ...information might be injected into the network because of defective sensors, malicious vehicles, and so on. Therefore, an efficient mechanism to guarantee the reliability of information used by vehicles is of great importance in vehicular networks. To solve this problem, this article proposes a context-awareness trust management model to evaluate the trustworthiness of messages received by vehicles to ensure bogus information will not influence the driving decision-making process. In the proposed scheme, the trust evaluation result of an evaluation request is determined by available related information and the evaluation strategy in the current situation, which is unaffected by the presence of conflicting evidence and the trust level of entities in the network. Moreover, we design a reinforcement learning model that allows vehicles to adjust the evaluation strategy so as to maintain an accurate evaluation result in different driving scenarios. Extensive experiments were conducted in different driving scenarios to verify the effectiveness of the proposed model. The results show that our model is adaptive to different driving scenarios with negligible time overhead, regardless of the proportion of malicious nodes in the network. Furthermore, compared with three types of state-of-the-art trust models in different scenarios, our scheme can achieve a higher evaluation precision rate with no more computational and communication overhead in nonrandom road conditions.
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