A Secured Message Transmission Protocol for Vehicular Ad Hoc Networks

Vehicular Ad hoc Networks(VANETs)become a very crucial addition in the Intelligent Transportation System(ITS).It is challenging for a VANET system to provide security services and parallelly maintain high throughput by utilizing limited resources.To overcome these challenges,we propose a blockchain-based Secured Cluster-based MAC(SCB-MAC)protocol.The nearby vehicles heading towards the same direction will form a cluster and each of the clusters has its blockchain to store and distribute the safety messages.The message which contains emergency information and requires Strict Delay Requirement(SDR)for transmission are called safety messages(SM).Cluster Members(CMs)sign SMs with their private keys while sending them to the blockchain to confirm authentication,integrity,and confidentiality of the message.A Certificate Authority(CA)is responsible for physical verification,key generation,and privacy preservation of the vehicles.We implemented a test scenario as proof of concept and tested the safety message transmission(SMT)protocol in a real-world platform.Computational and storage overhead analysis shows that the proposed protocol for SMT implements security,authentication,integrity,robustness,non-repudiation,etc.while maintaining the SDR.Messages that are less important compared to the SMs are called non-safety messages(NSM)and vehicles use RTS/CTS mechanism for NSM transmission.Numerical studies show that the proposed NSM transmission method maintains 6 times more throughput,2 times less delay and 125%less Packet Dropping Rate(PDR)than traditional MAC protocols.These results prove that the proposed protocol outperforms the traditional MAC protocols.

VDCM: A Data Collection Mechanism for Crowd Sensing in Vehicular Ad Hoc Networks

With the rapid development of mobile devices,aggregation security and efficiency topics are more important than past in crowd sensing.When collecting large-scale vehicle-provided data,the data transmitted via autonomous networks are publicly accessible to all attackers,which increases the risk of vehicle exposure.So we need to ensure data aggregation security.In addition,low aggregation efficiency will lead to insufficient sensing data,making the data unable to provide data mining services.Aiming at the problem of aggregation security and efficiency in large-scale data collection,this article proposes a data collection mechanism(VDCM)for crowd sensing in vehicular ad hoc networks(VANETs).The mechanism includes two mechanism assumptions and selects appropriate methods to reduce consumption.It selects sub mechanism 1 when there exist very few vehicles or the coalition cannot be formed,otherwise selects sub mechanism 2.Single aggregation is used to collect data in sub mechanism 1.In sub mechanism 2,cooperative vehicles are selected by using coalition formation strategy and auction cooperation agreement,and multi aggregation is used to collect data.Two sub mechanisms use Paillier homomorphic encryption technology to ensure the security of data aggregation.In addition,mechanism supplements the data update and scoring steps to increase the amount of available data.The performance analysis shows that the mechanism proposed in this paper can safely aggregate data and reduce consumption.The simulation results indicate that the proposed mechanism reduces time consumption and increases the amount of available data compared with existing mechanisms.

On the security of warning message dissemina-tion in vehicular Ad hoc networks

Information security is an important issue in vehicular networks as the accuracy and integrity of information is a prerequisite to the satisfactory performance of virtually all vehicular network applications.We study the information security of a vehicular Ad hoc network whose message could be tampered by malicious vehicles.An analytical framework is developed to analyze the process of message dissemination in a vehicular network with malicious vehicles randomly distributed in the network.The probability that a destination vehicle at a xed distance can receive the message correctly from the source vehicle is obtained.Simulations are conducted to validate the accuracy of the theoretical analysis.Our results demonstrate the impact of network topology and the distribution of malicious vehicles on the correct delivery of a message in vehicular Ad hoc networks,and provides insight on the design of security mechanisms to improve the security of message dissemination in vehicular networks.

Data dissemination model using Epidemic and Transmission-Segment-based Geographic Routing protocol:a new perspective in vehicular ad hoc networks

Purpose-The purpose of this paper is to introduce a new data dissemination model in order to improve the performance of transmission in VANET.It proposes a protocol named Epidemic and Transmission-Segmentbased Geographic Routing(ETSGR)and outlining the issues due to high mobility of nodes and uncertain physical topologies in the network.The proposed ETSGR is mainly used to analyze the vehicle state,direction,distance,traffic density and link quality of the network.Design/methodology/approach-This research work based on ETSGR protocol mainly uses epidemic algorithmin order to find the vehicle state based on susceptible,infected and recovered(SIR)model.Furthermore,the vehicle position and finding the head node in the network is utilized using the transmission segment protocol based on geographic routing and analyses each node to formthe segments and find the destination to transmit the data in timely manner.Findings-The paper provides the enhancement of the performance based on some metrics such as end-to-end delaythat obtained 0.62%,data throughput as 32.3%,packetdelivery ratio as 67%and one-hop communicationas 13%.The proposed ETSGR protocolanalyzes the state of the vehiclecorrectly and each node segmented to transmit the data with the timely manner and obtaining reliable performanceeven with highmobility of nodes in the network.Research limitations/implications-The proposed ETSGR protocol may have some limitation when considering the timing which should improve even in increasing many number of vehicles and different road segments.Practical implications-This paper includes some suggestions for the practical deployment of the approach in which a real-time traffic analysis can be evaluated for taking prior actions during an emergency situation and proper dissemination of data in timely manner can help utilize the guidance of proper planning of roads.Originality/value-This research fulfills an enhanced protocol to improve the performance of data dissemination.

A Review on the Recent Trends of Image Steganography for VANET Applications

Image steganography is a technique of concealing confidential information within an image without dramatically changing its outside look.Whereas vehicular ad hoc networks(VANETs),which enable vehicles to communicate with one another and with roadside infrastructure to enhance safety and traffic flow provide a range of value-added services,as they are an essential component of modern smart transportation systems.VANETs steganography has been suggested by many authors for secure,reliable message transfer between terminal/hope to terminal/hope and also to secure it from attack for privacy protection.This paper aims to determine whether using steganography is possible to improve data security and secrecy in VANET applications and to analyze effective steganography techniques for incorporating data into images while minimizing visual quality loss.According to simulations in literature and real-world studies,Image steganography proved to be an effectivemethod for secure communication on VANETs,even in difficult network conditions.In this research,we also explore a variety of steganography approaches for vehicular ad-hoc network transportation systems like vector embedding,statistics,spatial domain(SD),transform domain(TD),distortion,masking,and filtering.This study possibly shall help researchers to improve vehicle networks’ability to communicate securely and lay the door for innovative steganography methods.

Secure and Reliable Routing in the Internet of Vehicles Network:AODV-RL with BHA Attack Defense

Wireless technology is transforming the future of transportation through the development of the Internet of Vehicles(IoV).However,intricate security challenges are intertwinedwith technological progress:Vehicular ad hoc Networks(VANETs),a core component of IoV,face security issues,particularly the Black Hole Attack(BHA).This malicious attack disrupts the seamless flow of data and threatens the network’s overall reliability;also,BHA strategically disrupts communication pathways by dropping data packets from legitimate nodes altogether.Recognizing the importance of this challenge,we have introduced a new solution called ad hoc On-Demand Distance Vector-Reputation-based mechanism Local Outlier Factor(AODV-RL).The significance of AODVRL lies in its unique approach:it verifies and confirms the trustworthiness of network components,providing robust protection against BHA.An additional safety layer is established by implementing the Local Outlier Factor(LOF),which detects and addresses abnormal network behaviors.Rigorous testing of our solution has revealed its remarkable ability to enhance communication in VANETs.Specifically,Our experimental results achieve message delivery ratios of up to 94.25%andminimal packet loss ratios of just 0.297%.Based on our experimental results,the proposedmechanismsignificantly improves VANET communication reliability and security.These results promise a more secure and dependable future for IoV,capable of transforming transportation safety and efficiency.

A RELIABILITY ENHANCED DENSITY ADAPTIVE DATA DISSEMINATION SCHEME FOR VANETS

In this paper,a reliability enhanced and density adaptive data disseminating scheme is proposed for Vehicular Ad hoc NETworks(VANETs).The distributed on demand inquiring and responding mechanism is employed to get nodes' connectivity information.The announcing-listening process is also designed to find the nodes with bigger additional degree to rebroadcast,by which the relaying node is selected freely from density's influence.Simultaneously,a reliability parameter is designed to choose redundant relays for each hop.According to the importance of the broadcast,the parameter is set by the source node properly.Simulation results show that the scheme has achieved good performances such as low forwarding ratio,short latency and low load.The broadcast coverage ratio is ensured against the influence of key link errors and relaying nodes failure by paying suitable additional communication.

The research of traffic density extraction method under vehicular ad hoc network environment

Purpose–Traffic density is one of the most important parameters to consider in the traffic operationfield.Owing to limited data sources,traditional methods cannot extract traffic density directly.In the vehicular ad hoc network(VANET)environment,the vehicle-to-vehicle(V2V)and vehicle-to-infrastructure(V2I)interaction technologies create better conditions for collecting the whole time-space and refined traffic data,which provides a new approach to solving this problem.Design/methodology/approach–On that basis,a real-time traffic density extraction method has been proposed,including lane density,segment density and network density.Meanwhile,using SUMO and OMNet11 as traffic simulator and network simulator,respectively,the Veins framework as middleware and the two-way coupling VANET simulation platform was constructed.Findings–Based on the simulation platform,a simulated intersection in Shanghai was developed to investigate the adaptability of the model.Originality/value–Most research studies use separate simulation methods,importing trace data obtained by using from the simulation software to the communication simulation software.In this paper,the tight coupling simulation method is applied.Using real-time data and history data,the research focuses on the establishment and validation of the traffic density extraction model.

Unicast routing protocols for urban vehicular networks:review, taxonomy, and open research issues

Over the past few years, numerous traffic safety applications have been developed using vehicular ad hoc networks(VANETs). These applications represent public interest and require network-wide dissemination techniques. On the other hand, certain non-safety applications do not require network-wide dissemination techniques.Such applications can be characterized by their individual interest between two vehicles that are geographically apart. In the existing literature, several proposals of unicast protocols exist that can be used for these non-safety applications. Among the proposals, unicast protocols for city scenarios are considered to be most challenging.This implies that in city scenarios unicast protocols show minimal persistence towards highly dynamic vehicular characteristics, including mobility, road structure, and physical environment. Unlike other studies, this review is motivated by the diversity of vehicular characteristics and difficulty of unicast protocol adaption in city scenarios.The review starts with the categorization of unicast protocols for city scenarios according to their requirement for a predefined unicast path. Then, properties of typical city roads are discussed, which helps to explore limitations in efficient unicast communication. Through an exhaustive literature review, we propose a thematic taxonomy based on different aspects of unicast protocol operation. It is followed by a review of selected unicast protocols for city scenarios that reveal their fundamental characteristics. Several significant parameters from the taxonomy are used to qualitatively compare the reviewed protocols. Qualitative comparison also includes critical investigation of distinct approaches taken by researchers in experimental protocol evaluation. As an outcome of this review, we point out open research issues in unicast routing.

A Robust Emergency Messages Routing Scheme for Urban VANETs

Vehicular ad-hoc networks(VANETs)play an essential role in enhancing transport infrastructure by making vehicles intelligent and proficient in preventing traffic fatalities.Direction-based greedy protocols pick the next route vehicle for transmitting emergency messages(EMs)depending upon the present location of adjacent vehicles towards sink vehicles by using an optimal uni-directional road traffic approach.Nevertheless,such protocols suffer performance degradation by ignoring the moving directions of vehicles in bi-directional road traffic where topological changes happen continuously.Due to the high number of vehicles,it is essential to broadcast EMs to all vehicles to prevent traffic delays and collisions.A cluster-based EM transmitting technique is proposed in this paper.For urban VANETs,this paper pioneers the clustering of bi-directional road traffic for robust and efficient routing of EMs.In this regard,this paper introduces a routing protocol,namely,the bi-directional urban routing protocol(BURP).In addition to the paths and relative locations of vehicles,BURP takes account of the distance parameter by using the Hamming distance function to determine the direction ofmotion of vehicles and communicates EMs through the cluster head(CH).Amodified k-medoids algorithm is presented for the clustering of bi-directional road traffic.A median method is presented for selecting CH to ensure the longrunning of a cluster.Simulation results show that BURP provides enhanced throughput,a maximized packet delivery ratio,low energy consumption,and network delay relative to eminent routing protocols.

Cooperative Channel Assignment for VANETs Based on Dual Reinforcement Learning

Dynamic channel assignment(DCA)is significant for extending vehicular ad hoc network(VANET)capacity and mitigating congestion.However,the un-known global state information and the lack of centralized control make channel assignment performances a challenging task in a distributed vehicular direct communication scenario.In our preliminary field test for communication under V2X scenario,we find that the existing DCA technology cannot fully meet the communication performance requirements of VANET.In order to improve the communication performance,we firstly demonstrate the feasibility and potential of reinforcement learning(RL)method in joint channel selection decision and access fallback adaptation design in this paper.Besides,a dual reinforcement learning(DRL)-based cooperative DCA(DRL-CDCA)mechanism is proposed.Specifically,DRL-CDCA jointly optimizes the decision-making behaviors of both the channel selection and back-off adaptation based on a multi-agent dual reinforcement learning framework.Besides,nodes locally share and incorporate their individual rewards after each communication to achieve regional consistency optimization.Simulation results show that the proposed DRL-CDCA can better reduce the one-hop packet delay,improve the packet delivery ratio on average when compared with two other existing mechanisms.

Reliable connectivity and efficient data dissemination in VANETs

Connectivity and data dissemination in vehicular ad hoc networks(VANETs)have recently received considerable attention.Due to the unique characteristics of VANETs,the network connectivity is poor and reliable transmission in VANETs is hard to achieve.In this paper,we analyze the connectivity of randomly deployed vehicles on a road in VANETs and show the relation among the connectivity,the vehicle density and the communication radius.The reliable data dissemination scheme based on assisted nodes is studied.The simulation results show our novel scheme increases the network performance in terms of data dissemination rate.

Applications of intelligent computing in vehicular networks

Purpose–This paper aims to introduce vehicular network platform,routing and broadcasting methods and vehicular positioning enhancement technology,which are three aspects of the applications of intelligent computing in vehicular networks.From this paper,the role of intelligent algorithm in thefield of transportation and the vehicular networks can be understood.Design/methodology/approach–In this paper,the authors introduce three different methods in three layers of vehicle networking,which are data cleaning based on machine learning,routing algorithm based on epidemic model and cooperative localization algorithm based on the connect vehicles.Findings–In Section 2,a novel classification-based framework is proposed to efficiently assess the data quality and screen out the abnormal vehicles in database.In Section 3,the authors canfind when traffic conditions varied from freeflow to congestion,the number of message copies increased dramatically and the reachability also improved.The error of vehicle positioning is reduced by 35.39%based on the CV-IMM-EKF in Section 4.Finally,it can be concluded that the intelligent computing in the vehicle network system is effective,and it will improve the development of the car networking system.Originality/value–This paper reviews the research of intelligent algorithms in three related areas of vehicle networking.In thefield of vehicle networking,these research results are conducive to promoting data processing and algorithm optimization,and it may lay the foundation for the new methods.

Adaptive green traffic signal controlling using vehicular communication

The importance of using adaptive traffic signal control for figuring out the unpredictable traffic congestion in today's metropolitan life cannot be overemphasized. The vehicular ad hoc network(VANET), as an integral component of intelligent transportation systems(ITSs), is a new potent technology that has recently gained the attention of academics to replace traditional instruments for providing information for adaptive traffic signal controlling systems(TSCSs). Meanwhile, the suggestions of VANET-based TSCS approaches have some weaknesses:(1) imperfect compatibility of signal timing algorithms with the obtained VANET-based data types, and(2) inefficient process of gathering and transmitting vehicle density information from the perspective of network quality of service(Qo S). This paper proposes an approach that reduces the aforementioned problems and improves the performance of TSCS by decreasing the vehicle waiting time, and subsequently their pollutant emissions at intersections. To achieve these goals, a combination of vehicle-to-vehicle(V2V) and vehicle-to-infrastructure(V2I) communications is used. The V2 V communication scheme incorporates the procedure of density calculation of vehicles in clusters, and V2 I communication is employed to transfer the computed density information and prioritized movements information to the road side traffic controller. The main traffic input for applying traffic assessment in this approach is the queue length of vehicle clusters at the intersections. The proposed approach is compared with one of the popular VANET-based related approaches called MC-DRIVE in addition to the traditional simple adaptive TSCS that uses the Webster method. The evaluation results show the superiority of the proposed approach based on both traffic and network Qo S criteria.

Context and Machine Learning Based Trust Management Framework for Internet of Vehicles

Trust is one of the core components of any ad hoc network security system.Trust management(TM)has always been a challenging issue in a vehicular network.One such developing network is the Internet of vehicles(IoV),which is expected to be an essential part of smart cities.IoV originated from the merger of Vehicular ad hoc networks(VANET)and the Internet of things(IoT).Security is one of the main barriers in the on-road IoV implementation.Existing security standards are insufficient to meet the extremely dynamic and rapidly changing IoV requirements.Trust plays a vital role in ensuring security,especially during vehicle to vehicle communication.Vehicular networks,having a unique nature among other wireless ad hoc networks,require dedicated efforts to develop trust protocols.Current TM schemes are inflexible and static.Predefined scenarios and limited parameters are the basis for existing TM models that are not suitable for vehicle networks.The vehicular network requires agile and adaptive solutions to ensure security,especially when it comes to critical messages.The vehicle network’s wireless nature increases its attack surface and exposes the network to numerous security threats.Moreover,internet involvement makes it more vulnerable to cyberattacks.The proposed TM framework is based on context-based cognition and machine learning to be best suited to IoV dynamics.Machine learning is the best solution to utilize the big data produced by vehicle sensors.To handle the uncertainty Bayesian machine learning statistical model is used.The proposed framework can adapt scenarios dynamically and infer using the maximum possible parameter available.The results indicated better performance than existing TM methods.Furthermore,for future work,a high-level machine learning model is proposed.

Security Analysis for a VANET Privacy Protection Scheme

Vehicular ad hoc network(VANET)is a self-organizing wireless sensor network model,which is extensively used in the existing traffic.Due to the openness of wireless channel and the sensitivity of traffic information,data transmission process in VANET is vulnerable to leakage and attack.Authentication of vehicle identitywhile protecting vehicle privacy information is an advantageous way to improve the security of VANET.We propose a scheme based on fair blind signature and secret sharing algorithm.In this paper,we prove that the scheme is feasible through security analysis.

V2V Online Data Offloading Method Based on Vehicle Mobility

As people are accustomed to getting information in the vehicles,mobile data offloading through Vehicular Ad Hoc Networks(VANETs)becomes prevalent nowadays.However,the impacts caused by the vehicle mobility(such as the relative speed and direction between vehicles)have great effects on mobile data offloading.In this paper,a V2V online data offloading method is proposed based on vehicle mobility.In this mechanism,the network service process was divided into continuous and equal-sized time slots.Data were transmitted in a multicast manner for the sake of fairness.The data offloading problem was formalized to maximize the overall satisfaction of the vehicle users.In each time slot,a genetic algorithm was used to solve the maximizing problem to obtain a mobile data offloading strategy.And then,the performance of the algorithm was enhanced by improving the algorithm.The experiment results show that vehicle mobility has a great effect on mobile data offloading,and the mobile data offloading method proposed in the paper is effective.

Cross-domain identity authentication scheme based on blockchain and PKI system

In vehicular ad hoc networks(VANET),the cross-domain identity authentication of users is very important for the development of VANET due to the large cross-domain mobility of vehicle users.The Public Key Infrastructure(PKI)system is often used to solve the identity authentication and security trust problems faced by VANET.However,the PKI system has challenges such as too centralized Authority of Certification Authority(CA),frequent cross-domain access to certificate interactions and high authentication volume,leading to high certificate management costs,complex cross-domain authentication paths,easy privacy leakage,and overburdened networks.To address these problems,this paper proposes a lightweight blockchain-based PKI identity management and authentication architecture that uses smart contracts to reduce the heavy burden caused by CAs directly managing the life cycle of digital certificates.On this basis,a trust chain based on smart contracts is designed to replace the traditional CA trust chain to meet the general cross-domain requirements,to effectively avoid the communication pressure caused by a mass of certificate transmissions.For the cross-domain scenario with higher privacy and security requirements the identity attribute authentication service is provided directly while protecting privacy by using the Merkle tree to anchor identity attribute data on and off the blockchain chain.Finally,the proposed scheme was comprehensively analyzed in terms of cost,time consumption and security.

A scalable blockchain-based scheme for traffic-related data sharing in VANETs

Recent advances in wireless technology and embedded systems enable vehicles to share relevant traffic-related data to improve the transportation Quality-of-Service(QoS).However,due to the ubiquitousness of cyber-attacks,it is challenging to ensure the integrity of the data collected from cars.This paper proposes a novel architecture for road traffic events management in Vehicular Ad hoc NETworks(VANETs)relying on a permissioned blockchain.It also introduces the concept of micro-transactions to minimize communication and storage overhead.Through simulations,a rigorous performance evaluation of the proposed approach was conducted,and the micro-transactions effectiveness was assessed.In addition,a comparison with close works in the literature was performed.The proposed scheme ensures road traffic records integrity and traceability,and simulation results on the considered scenarios showed good performance.