Vehicular Ad Hoc Networks Environment Research Articles

Secure and Efficient Communication in VANETs Using Level-Based Access Control

In recent years, the development of vehicular ad-hoc networks (VANETs) has received much attention in intelligent transportation systems (ITS). Unlike traditional ad-hoc networks, VANETs are emerging with unique characteristics that share similar technology with autonomous vehicles (AVs) and automated driving systems (ASDs). Communication between vehicles and the surrounding infrastructure unit, such as a roadside unit (RSU), must be secured, concise, and authentic. Hence, an access control system for the ad-hoc environment is required. We introduced a level-based controlled signcryption (LBS) scheme, which can be easily constructed and implemented into an access control system for VANETs environment. Our encrypted message has a short and constant size, which is better when compared with other attribute-based signcryption or encryption. Confidentiality, privacy, and authenticity are also provided in our scheme to ensure secure and authentic communication. Therefore, our scheme has addressed communication cost, scalability, security, and privacy issues in VANETs. This primitive can be applied to simplify attribute-based access control, as the only attribute required is an integer representing the security level. Our objective is to improve the quality and security of VANET communication. Moreover, an optional privacy mechanism in our scheme provides flexibility in controlling node privacy in VANETs.

ECLAS: An Efficient Pairing-Free Certificateless Aggregate Signature for Secure VANET Communication

Vehicular ad hoc networks (VANETs) have become an important part of the intelligent transportation system that aims to promote communication among vehicles to ensure vehicular safety and improve the driving experience. In VANETs, signed messages need to be authenticated by roadside units in a very short time. Certificateless aggregate signature (CLAS) scheme has been considered as one of the promising solutions to solve the problem of limited network bandwidth and computing power in VANETs environment. In this article, we propose an efficient pairing-free CLAS, named eCLAS, which is suitable for communication between vehicle to infrastructure. The aggregated signature allows individual signature on different messages from different vehicles to be aggregated into one short signature. In the random oracle model, the security of the scheme is proved by the adaptive selection message attack and the difficulty of computation of discrete logarithm problem on the elliptic curve. Additionally, the security analysis shows that the proposed scheme can meet security requirements in VANETs. Compared with existing schemes, the result demonstrates that our scheme has obvious advantages in signature verification, thereby granting it better applicability.

An optimized deep learning-based trust mechanism In VANET for selfish node detection

PurposeThis study aims to develop a trust mechanism in a Vehicular ad hoc Network (VANET) based on an optimized deep learning for selfish node detection.Design/methodology/approachThe authors built a deep learning-based optimized trust mechanism that removes malicious content generated by selfish VANET nodes. This deep learning-based optimized trust framework is the combination of the Deep Belief Network-based Red Fox Optimization algorithm. A novel deep learning-based optimized model is developed to identify the type of vehicle in the non-line of sight (nLoS) condition. This authentication scheme satisfies both the security and privacy goals of the VANET environment. The message authenticity and integrity are verified using the vehicle location to determine the trust level. The location is verified via distance and time. It identifies whether the sender is in its actual location based on the time and distance.FindingsA deep learning-based optimized Trust model is used to detect the obstacles that are present in both the line of sight and nLoS conditions to reduce the accident rate. While compared to the previous methods, the experimental results outperform better prediction results in terms of accuracy, precision, recall, computational cost and communication overhead.Practical implicationsThe experiments are conducted using the Network Simulator Version 2 simulator and evaluated using different performance metrics including computational cost, accuracy, precision, recall and communication overhead with simple attack and opinion tampering attack. However, the proposed method provided better prediction results in terms of computational cost, accuracy, precision, recall, and communication overhead than other existing methods, such as K-nearest neighbor and Artificial Neural Network. Hence, the proposed method highly against the simple attack and opinion tampering attacks.Originality/valueThis paper proposed a deep learning-based optimized Trust framework for trust prediction in VANET. A deep learning-based optimized Trust model is used to evaluate both event message senders and event message integrity and accuracy.

Efficient and Secure Remote Health Management in Cloud in Vehicular Adhoc Network Environment

Vehicle Ad Hoc Networks (VANETs) is a crucial communications framework for transferring messages between any healthcare systems. The dilemma of fixing the safest efficient route is a tedious issue in VANET. Hence the secure and most reliable way will give the appropriate solution for the routing issues in the VANET. In this paper, by using the Multi-Objective Bio-inspired Heuristic Cuckoo Search Node optimization algorithm is designed to find the efficient safest route for transferring health data within a short period. After seeing the efficient route, the node can be distinguished upon the traffic and security by using the Stochastic Discriminant Random Forest Node Classifier. Then in the selected route, the nodal distance can be calculated by applying the delay-based weighted end-to-end approach for traffic analysis. Then the authentic vehicle node can be analyzed through the Trust Aware extreme Gradient Boosting Node Classification based Secured Routing (TAXGBNC-SR) Technique. The obtained information that can be stored in the cloud. It deal with the multiple number of tasks gives to the ARM micro-controllers in order to perform the multiple tasks that gets logged in the cloud via Internet of Things technology (Iot).

Blockchain-Based Authentication in Internet of Vehicles: A Survey.

Internet of Vehicles (IoV) has emerged as an advancement over the traditional Vehicular Ad-hoc Networks (VANETs) towards achieving a more efficient intelligent transportation system that is capable of providing various intelligent services and supporting different applications for the drivers and passengers on roads. In order for the IoV and VANETs environments to be able to offer such beneficial road services, huge amounts of data are generated and exchanged among the different communicated entities in these vehicular networks wirelessly via open channels, which could attract the adversaries and threaten the network with several possible types of security attacks. In this survey, we target the authentication part of the security system while highlighting the efficiency of blockchains in the IoV and VANETs environments. First, a detailed background on IoV and blockchain is provided, followed by a wide range of security requirements, challenges, and possible attacks in vehicular networks. Then, a more focused review is provided on the recent blockchain-based authentication schemes in IoV and VANETs with a detailed comparative study in terms of techniques used, network models, evaluation tools, and attacks counteracted. Lastly, some future challenges for IoV security are discussed that are necessary to be addressed in the upcoming research.

VTrust: An IoT-Enabled Trust-Based Secure Wireless Energy Sharing Mechanism for Vehicular Ad Hoc Networks.

Vehicular Ad hoc Network (VANET) is a modern concept that enables network nodes to communicate and disseminate information. VANET is a heterogeneous network, due to which the VANET environment exposes to have various security and privacy challenges. In the future, the automobile industry will progress towards assembling electric vehicles containing energy storage batteries employing these resources to travel as an alternative to gasoline/petroleum. These vehicles may have the capability to share their energy resources upon the request of vehicles having limited energy resources. In this article, we have proposed a trust management-based secure energy sharing mechanism, named vTrust, which computes the trust degree of nodes to authenticate nodes. The proposed mechanism is a multi-leveled centralized approach utilizing both the infrastructure and vehicles to sustain a secure environment. The proposed vTrust can aggregate and propagate the degree of trust to enhance scalability. The node that requests to obtain the energy resources may have to maintain a specified level of trust threshold for earning resources. We have also evaluated the performance of the proposed mechanism against several existing approaches and determine that the proposed mechanism can efficiently manage a secure environment during resource sharing by maintaining average malicious nodes detection of 91.3% and average successful energy sharing rate of 89.5%, which is significantly higher in comparison to the existing approaches.

Efficient Privacy-Preserving Authentication Scheme With Fine-Grained Error Location for Cloud-Based VANET

As an emerging technology, cloud-based Vehicular Ad-Hoc Network (VANET) can significantly improve the efficiency of transportation systems by alleviating traffic congestion and optimizing resource management. However, since the information transmitted in VANET is distributed in an open-access environment, security and privacy are now becoming vital concerns, especially when attackers own more and more resources. Recently, many tamper-proof devices (TPD)-based authentication schemes have been proposed to tackle the above-mentioned challenges, while most of them are dependent on ideal TPDs with very strong security assumptions. Moreover, when the aggregate signature verification fails, these schemes can do nothing but discard the aggregate signature completely, which makes them impractical in VANET. To address the above concerns, we propose a more realistic TPD-based authentication scheme with privacy-preserving features for cloud-based VANET. Specifically, the off-line self-updating method is utilized to update the data in TPD periodically to resist side-channel attacks. Furthermore, an efficient fine-grained error location algorithm is designed to quickly detect all invalid signatures within a problematic aggregate signature scenario. Our performance analysis shows that the proposed scheme outperforms the existing ones in terms of security, computation delay and communication overhead, thus more suitable in practical cloud-based VANET environment.

Strong key-insulated secure and energy-aware certificateless authentication scheme for VANETs

The rise of vehicular ad-hoc networks (VANETs) brings promise for guaranteeing road safety and improving traffic efficiency. Nevertheless, the pity is that the problems, such as messages authentication and privacy-preserving, that come with it seriously threaten the security and stability of the VANETs. For addressing these problems, in this paper, a pairing-free certificateless signature work for VANETs that supports parallel key-insulated is constructed. On the one hand, the presented work is constructed utilizing the elliptic curve rather than the costly pairing operation. In this way, each vehicle can generate or verify authentication message in a low energy consumption manner. On the other hand, the mechanism of parallel key-insulated is introduced in our proposed work where two helpers alternately assist the users for the periodical key updates, which can not only resist the key exposure but also reduce the risk of the helper’s secret key exposure. Considering possible key exposure in the high dynamic VANETs scenarios, our scheme is more stable and feasible for VANETs environments compared with the existing works. Finally, our work is proved to be strongly key-insulated secure under the discrete logarithm assumption in the random oracle model. Meanwhile, the detailed performance comparisons demonstrate that our work is energy efficient and practical for VANET.

Payoff-based Dynamic Segment Replication and Graph Classification Method with Attribute Vectors Adapted to Urban VANET

Due to the number of constraints and the dynamic nature of vehicular ad hoc networks (VANET), effective video broadcasting always remains a difficult task. In this work, we proposed a quality of video visualization guarantee model based on a feedback loop and an efficient algorithm for segmenting and replicating video segments using the Payoff-based Dynamic Segment Replication Policy (P-DSR). In the urban VANET environment, P-DSR is defined by taking into account the position of the vehicles, the speed, the direction, the number of neighboring vehicles, and the reputation of each node to stabilize the urban VANET topology. However, the management of various load control parameters between the different components of the urban VANET network remains a problem to be studied. This work uses a multi-objective problem that takes the parameters of our algorithm based on the Graph Classification Method with Attribute Vectors (GCMAV) as input. This algorithm aims to provide an improved class lifetime, an improved video segment delivery rate, a reduced inter-class overload, and an optimization of a global criterion. A scalable algorithm is used to optimize the parameters of the GCMAV. The simulations were carried out using the NetSim simulator and Multi-Objective Evolutionary Algorithms framework to optimize parameters. Experiments were carried out with realistic maps of Open Street Maps and its results were compared with other algorithms such as Seamless and Authorized Multimedia Streaming and P-DSR. The survey suggests that the proposed methodology works well concerning the average lifetime of the inter-classes and the delivery rate of video segments.

Research on Manhattan Distance Based Trust Management in Vehicular Ad Hoc Network

In recent years, Vehicular Ad Hoc Network (VANET) has developed significantly. Coordination between vehicles can enhance driving safety and improve traffic efficiency. Due to the high dynamic characteristic of VANET, security has become one of the challenging problems. Trust of the message is a key element of security in VANET. This paper proposes a Manhattan Distance Based Trust Management model (MDBTM) in VANET environment which solves the problem in existing trust management research that considers the distance between the sending vehicle and event location. In this model, the Manhattan distance and the number of building obstacles are calculated by considering the movement relationship between the sending vehicle and event location. The Dijkstra algorithm is used to predict the path with the maximum probability, when the vehicle is driving toward the event location. The message scores are then calculated based on the Manhattan distance and the number of building obstacles. Finally, the scores are fused to determine whether to trust the message. The experimental results show that the proposed method has better performance than similar methods in terms of correct decision probability under different proportions of malicious vehicles, different numbers of vehicles, and different reference ranges.

Reinforcement Technique for Deploying Intelligent Delay Tolerant Network

The erratic environment of Vehicular ad-hoc network (VANET), specifically in challenged areas like military or battle fields, may lose the data while forwarding certain important multimedia files. As we know Vehicular Delay Tolerant Network (VDTNs) lack permanent grid power connections so to optimize the use of the power of nodes, reinforcement learning techniques to can be applied to the base stations/roadside units (RSUs). The RSUs learn to pick a vehicle based on information gathered about traffic characteristics, budget for infrastructure resources, and the total duration of a contact time. Based on the cumulative knowledge a compensation metric is evaluated. This acts as a performance metric to determine which vehicular node to select for message forwarding. To make decisions based on observations made by RSUs analyses by applying deep reinforcement learning augments. This saves the power of the nodes. This novel energy efficient technique by deploying secure, intelligent mechanisms in the vehicular nodes is proposed, which significantly improves the processing of files in the challenges networks. For simulation purpose, a real-time data set is taken from the crawdad website. Experimental results show that after applying reinforcement technique, there is an increase in 28% of message delivery, decrease in latency of 16% and reduction of 21% in energy consumption.

Dynamic Environment Improvement for Vanets

Vehicular Ad-Hoc Network (VANET) are dynamic network because no fixed topology available in this environment, in this paper we try to check VANET environment and studied how we create the message with the help of simulator and send message source to destination simulator used dedicated short range protocol (DSRC) for communication. We check the efficiency of the environment and collect the data for improvement of the network.

PLVA: Privacy-Preserving and Lightweight V2I Authentication Protocol

Vehicular ad hoc networks (VANETs) significantly improves the efficiency and safety of driving since it reduces traffic jams and avoiding accidents, in which the necessary security goals are guaranteed using cryptographic method. In reality, the computation efficiency is very important in implementing the protocol in VANETs. When a vehicle with high speed enters in the coverage of a roadside unit (RSU), the computation overhead of authentication not only affects the communication experience, but also downgrades the driving safety. The feasible solution is to share a message in advance between vehicle and RSU with the help of certification authority (CA), however, CA can deduce the vehicle’s route that should be privacy. In this paper, a privacy-preserving and lightweight V2I authentication (PLVA) protocol is proposed. Specifically, in the beginning phase, all roadside units in a region are converted to a vector using the Moore curve technique, then, a vehicle deduces the RSUs’ information on its planning route using BGN homomorphic encryption before the vehicle begins its trip, meanwhile, CA knows nothing about the route plan although it assists the above process. With the deduced RSUs’ information, fast authentication is achieved between vehicle and each RSU on its route. Moreover, performance evaluation illustrates that our PLVA is efficient in practical VANETs environment.

Study on QoS Management for Video Streaming in Vehicular Ad Hoc Network (VANET)

Vehicular Ad Hoc Network (VANET) is a particular type of MANET providing various wireless communications such as infrastructure communications and inter-vehicle communications. Recently, VANET networks are attracting ample attention from the scientific and business community. In VANET networks, the textual data is almost negligible compared to the multimedia data that is interactive and expressive. Quality management of video streaming over the VANET environment is a complex task, given the specific constraints of multimedia data in terms of Quality of Service (QoS), security, system performance, and a random number of vehicles. This article discusses existing video streaming techniques in VANET networks by highlighting different QoS and Quality of Experience (QoE) metrics related to video streaming. A comparative study of video streaming models of literature on VANET is presented, taking into consideration several QoS and QoE metrics. Finally, the trends in video broadcasting in VANET networks are identified as future research directions. We believe that our comprehensive survey will enhance the understanding of video streaming tasks in the VANET environment and provide useful knowledge about the research trends and directions. VANET environment and provide useful knowledge about the research trends and directions.

A Novel Privacy‐Preserving Authentication Protocol Using Bilinear Pairings for the VANET Environment

With the rapid development of communication and microelectronic technology, the vehicular ad hoc network (VANET) has received extensive attention. However, due to the open nature of wireless communication links, it will cause VANET to generate many network security issues such as data leakage, network hijacking, and eavesdropping. To solve the above problem, this paper proposes a new authentication protocol which uses bilinear pairings and temporary pseudonyms. The proposed authentication protocol can realize functions such as the identity authentication of the vehicle and the verification of the message sent by the vehicle. Moreover, the proposed authentication protocol is capable of preventing any party (peer vehicles, service providers, etc.) from tracking the vehicle. To improve the efficiency of message verification, this paper also presents a batch authentication method for the vehicle to verify all messages received within a certain period of time. Finally, through security and performance analysis, it is actually easy to find that the proposed authentication protocol can not only resist various security threats but also have good computing and communication performance in the VANET environment.

An Efficient Routing Protocol Using an Improved Distance-Based Broadcasting and Fuzzy Logic System for VANET

The high mobility and frequent changes in the network topology remain a great divergence between Vehicular Ad-hoc Network (VANET) and Mobile Ad-hoc Network (MANET). This makes existing routing protocols for MANET imperfect for a VANET environment. In order to ensure good data transmission between vehicles, it is mandatory to improve these protocols to this new environment. Ad-hoc On-demand Distance Vector (AODV) is one of the most proposed reactive protocols in the literature for MANET, but its direct application in VANET returns poor performance results. In this paper, we propose an Efficient Routing Protocol using an improved Distance-Based Broadcasting and Fuzzy Logic System (ERPFL), which is an extension of the AODV routing protocol. In the first, the proposed scheme uses an improved Distance-Based Broadcasting method in route discovery process. Each vehicle selects the most suitable neighbours to send a route request, using different mobility parameters such as distance, velocity and direction. Then, the destination vehicle selects the best route from the most reliable routes received, using the Fuzzy Logic System. Link Expiration Time and Link Reliability Model are considered input metrics for this system. The simulation results show that ERPFL saves network bandwidth resources which contributes to a higher data transmission ratio. In addition, our proposed protocol efficiently distributes data packets, decreases the hop count and reduces network routing time.

Data Mining Method of Sequential Patterns for Vehicle Trajectory Prediction in VANET

In order to provide the future direction of vehicle flow for travelers, it is necessary to predict the driving trajectory of vehicles running on the road in a certain segments. According to the characteristics of vehicle sequential pattern, the topology of vehicular ad hoc network (VANET) is linked to the real road vehicle movement trajectory. Some new definitions related to sequential patterns in VANET environment are proposed. Based on RSU and V2V schemes, a vehicle movement database is established, and sequential pattern data mining is carried out. Afterward, their communication overhead is evaluated. The support and confidence of the movement rules generated by vehicle routing patterns are calculated to extract the probability of frequent driving trajectories.

Enhancing Location Privacy for Vehicular Ad Hoc Networks

Communication messages in Vehicular Ad-hoc Networks (VANETs) can be used to track movement of vehicles. In this paper, we address the problem of movement tracking and enhance location privacy without affecting security and safety of vehicles. By considering unique characteristics of VANETs, we firstly propose a synchronized pseudonym changing protocol based on the concept of forming groups among neighboring vehicles. Secondly, we analytically evaluate the anonymity and unlinkability of the proposed protocol. Finally, we do a series of simulations to evaluate the performance of our protocol in real VANET environments such as Manhattan and Urban. Simulation results show that our protocol is feasible and produces excellent performances. The main advantages of our protocol compared with the existing approaches include: 1) it makes larger anonymity set and higher entropy; 2) it reduces the tracking probability; 3) it can be used in both safety and non-safety communications; and 4) Vehicles need not suspend regular communication for changing pseudonyms.

VANET applications: Past, present, and future

Vehicular Ad-hoc Networks (VANETs) are an emerging technology that has much potential development ahead of it. VANETs seek to connect devices contained within vehicles together to create services that are particularly relevant to a vehicular environment. They attempt to do so without relying on infrastructure devices to assist in the process of network topology management. This particular nature of VANETs leads them to provide both unique challenges and opportunities to investigate. This paper will seek to address the key features that define a VANET environment, while discussing what can be done with a VANET system. This paper will then investigate many different perspectives on VANETs, including historical perspectives and ideas for uses as well as more modern perspectives, and discuss how they have changed over time. Finally, this paper will investigate the current state of VANET technologies and discuss the current progress towards the successful deployment of these technologies in the real world.

SAES: A self-checking authentication scheme with higher efficiency and security for VANET

Vehicular Ad Hoc Network (VANET), a wireless network for V2X communication, provides a new opportunity to create a safer, comfortable and efficient traffic environment. However, the large scale and open environment of VANET brings many problems and challenges to information security, especially the vehicular authentication problem. Many existing authentication schemes always used complex cryptographic algorithms in the process of vehicular authentication to avoid the leak of users’ privacy information. Nevertheless, these schemes are unsuitable for VANET due to its higher computational overhead, because VANET’s environments are characterized by short communication time between the vehicles and the Road-Side Units (RSUs). Therefore, efficiency and security should be fully considered during the process of vehicular authentication. This paper proposed A Self-checking Authentication Scheme with Higher Efficiency and Security for VANET, named SAES. The proposed scheme adopts self-checking authentication based on pseudonym instead of traditional authentication with the Trusted Authority (TA) participating in the authentication process to minimize the authentication cost. Meanwhile, the group signature is used to reduce the frequency of authentication for legitimate vehicles. The security and performance results of the proposed scheme, analyzed by the provable security and simulation, indicate that this scheme not only meets the requirements of security for VANET but also has a better performance in comparison with existing schemes.