Nodes In VANET Research Articles

Decentralized Distance-based Strategy for Detection of Sybil Attackers and Sybil Nodes in VANET

Decentralized Distance-based Strategy for Detection of Sybil Attackers and Sybil Nodes in VANET

Evaluating multidimensional RSSI-based approaches for identifying Sybil nodes in VANETs to improve vehicle network security

Evaluating multidimensional RSSI-based approaches for identifying Sybil nodes in VANETs to improve vehicle network security

A blockchain-based reputation system for trusted VANET nodes

Vehicular network applications, such as Local Danger Warnings (LDW), have become necessary as they provide services to drivers with warnings and instructions to ensure safe driving. However, before any vehicle reacts to an alert, it is essential to verify its veracity because an incorrect warning misleads other vehicles and causes unnecessary delays and detours in traffic. On the other hand, ignoring an alert or taking too long to verify it can cause accidents. A common way to address this problem is via a reputation system, where the veracity and plausibility of an alert message are assessed based on the reputation of the vehicle that discloses it. This paper describes a decentralized reputation system based on a consortium blockchain and smart contracts called BRS4VANETs. This system analyzes the reliability of data generated by a vehicle, detects malicious behavior, and contributes to decision-making. The complete functional architecture of the system, detailing the algorithms, evaluation metrics, communication protocol, and message formats, is described and implemented. Experiments with network and traffic simulators evaluated the risk of a false message attack, the effectiveness of the system and its overheads. The assessment demonstrates the importance of reputation systems and also shows the feasibility of having a decentralized system to store and disseminate reputation information based on blockchain technologies. Finally, the results also demonstrate that BRS4VANETs can successfully detect suspicious and malicious vehicles.

An Enhanced K Nearest Neighbor Classifier for Malicious Node Detection in VANET

Recently, wireless communication technologies have become a vital part of our lives. The advancements made in communication technology, VANET systems is been introduced. With the increase of vehicles, different sorts of traffic are created in realistic environment. In some cases, the traffic is created by anomalies. Henceforth, the security of VANET communication becomes an important entity. In this paper, we proposed an enhanced k-Nearest Neighbor classifier that detected the malicious node in VANET. Generally, the classifier suffers from high computational cost in distance estimation during malicious node detection. The efficiency of the proposed classifier is experimented and implemented by validating the throughput and packet delivery rate. Compared to the existing classifier, the proposed classifier achieves 20-25% improvement. By doing so, the communication overhead and delay metrics have been achieved and also helps to minimize the computational storage costs.

A collaborative strategy for detection and eviction of Sybil attacker and Sybil nodes in VANET

SummaryVehicular ad hoc network (VANET) is a part of the intelligent transportation system (ITS) that provides safety and nonsafety applications. The high mobility of vehicles and the wireless communication environment in VANET makes it vulnerable to various attacks. One among them is the Sybil attack, where a Sybil attacker creates multiple fake identities called Sybil nodes that disrupt the functionality of VANET. Most of the existing solutions in the literature discuss identifying the Sybil nodes (virtual); very few works exist to determine the Sybil attacker (source node that generates Sybil nodes). In this paper, we propose a computation less heuristic approach that focuses on detecting the Sybil attacker and its Sybil nodes using signal strength measurements and Euclidean distance as the detection parameters. The central VANET server, Road Side Units (RSUs), and vehicles collaborate in the detection process, which improves the accuracy of our approach. The core of the approach is a reward‐based system, where the vehicle rewards are determined by collecting RSUs' feedback about the vehicle behavior. From simulation experiments, it is evident that our proposed approach achieves a maximum detection rate of 99.89% and a false positive rate of 0.012% than the existing techniques.

Cybersecurity in Intelligent Transportation Systems

Intelligent Transportation Systems (ITS) are emerging field characterized by complex data model, dynamics and strict time requirements. Ensuring cybersecurity in ITS is a complex task on which the safety and efficiency of transportation depends. The imposition of standards for a comprehensive architecture, as well as specific security standards, is one of the key steps in the evolution of ITS. The article examines the general outlines of the ITS architecture and security issues. The main focus of security approaches is: configuration and initialization of the devices during manufacturing at perception layer; anonymous authentication of nodes in VANET at network layer; defense of fog-based structures at support layer and description and standardization of the complex model of data and metadata and defense of systems, based on AI at application layer. The article oversees some conventional methods as network segmentation and cryptography that should be adapted in order to be applied in ITS cybersecurity. The focus is on innovative approaches that have recently been trying to find their place in ITS security strategies. These approaches includes blockchain, bloom filter, fog computing, artificial intelligence, game theory and ontologies. In conclusion, a correlation is made between the commented methods, the problems they solve and the architectural layers in which they are applied.

Malicious Route Detection in Vehicular Ad-hoc Network using Geographic Routing with Masked Data

Background:Vehicular Ad-hoc Network is the subset of Mobile Ad-hoc Network, Intelligent Transport System and Internet of Things. The acting nodes in VANET are the vehicles on the road at any moment.Objective:The anonymity character of these vehicles is opening the opportunity for malicious attacks. Malicious routes increase the data retransmission and hence, the performance of routing will be degraded. The main objective this work is to identify the malicious routes, avoid the data transmission using these routes and increase the packet delivery ratio.Methods:In the proposed system called Geographic Routing Protocol with Masked data, two binary- codes called mask and share have been generated to identify the malicious route. The original data is encoded using these binary-codes and routed to the destination using the geographic routing protocol. It is reconstructed at the destination node and based on the encoding technique the malicious routes and malicious nodes are identified. Simulations were conducted with varying speed and varying network size in 20 km2 geographical area.Results:The average packet delivery ratio with varying speed is 0.817 and with varying networksize is 0.733.Conclusion:The proposed geographical routing protocol with masked data technique outperforms than traditional geographic protocol and Detection of Malicious Node protocol, by 0.102 and 0.264 respectively with different speeds and by 0.065 and 0.1616 respectively with different network size.

Routing Protocols in Vehicle Ad-Hoc Network

Vehicular Ad-hoc Network (VANET) is associate rising autonomous dynamic topology network. It is a unique type of Mobile Ad-hoc Network during which the automobiles amendment their message with each other. VANET turns every automobile in it into a mobile node and use those nodes to make a mobile dynamic community. The aim of VANET is to produce a wi-fi connectivity and numerous programs applications like collision dodging, safety and rising the traffic ratio as designing by the Intelligent Transportation System (ITS). The transport are strained by the sensible traffic surroundings, and currently the simulations are primarily network simulations that cannot simulate the real hint of the object (vehicle). Merely as nodes in VANETS have identical excessive mobility, so there are masses of demanding situation to route the packets to there final destination which need to be addressed by means of existing/offering new solutions for the comparable. Keeping view of above, In this paper, summarize the prevailing VANET routing protocols and classify and evaluate them. Then, listing numerous classic routing algorithms and examine their characteristics and advantages and disadvantages. Eventually, by way of analyzing the reputation of vehicle-installed routing protocols, we tend to illustrate the difficulties and challenges that vehicle-mounted routing protocols can/will encounter within the future.

VANETs Cloud: Architecture, Applications, Challenges, and Issues

Vehicles which are the nodes in VANETs are equipped with powerful resources to enable the safe and quick dissemination of information for reliable and trusty intelligent transportation system. These resources of vehicles can be utilized for providing support to various other new VANETs applications for enhancing the driving experience, reducing the road congestions, accidents and to promote pollution-free ITS. In order to support and promote the abovementioned tasks, a concept of vehicular cloud is getting a lot of attention nowadays. Introduction of VANETs cloud has led to the expansion in the perimeter of the capabilities of VANETs and ITS by enabling newer types of collaborations between the vehicles and also given rise to a plethora of emerging applications and services. In this study, an in-depth review covering all the possible aspects associated with VANETs cloud has been explored. To begin with, concepts like architectures, communication types supported in VANETs cloud has been analyzed. A motivation explaining the need of VANETs cloud in today’s scenario has been briefly overviewed. Then, a detailed comparison illustrating the similarities and differences between the VANETs cloud and its parent’s network i.e. VANETs is presented. In this article, our main focus is on finding the various applications that will be supported by VANETs cloud. Various challenges in terms of security, deployment and in the use of VANETs cloud has been explored. Finally, applicability of VANETs cloud with various emerging technologies like IoT, software defined networks, and cognitive radio in terms of their applications, challenges, issues, and benefits has been presented in this article. This study on the collaboration of VANETs and cloud is believed to assist the researchers working on this field to find out the current status of research in VANETs clouds along with the challenges that one can face during its deployment.

Link survivability rate-based clustering for QoS maximisation in VANET

A clustering technique is used in VANET to manage and stabilise topology information. Data communication in the cluster is performed by Cluster Heads (CH). The major issues involved in the clustering approaches are improper definition of cluster structure and maintenance of cluster structure in dynamic networks. To overcome these issues a link and weight-based clustering approach is developed along with Distributed Dispatching Information Table (DDIT). It is based on relative velocity of two same directional vehicles by forming a cluster with a number of nodes in VANET. The cluster head is selected based on link survival rate of the vehicles to provide the emergency message towards different vehicles in the cluster along with stored data packet information in DDIT table for fault prediction. Finally, an efficient medium access control protocol is used to provide prioritised message for avoiding spectrum shortage of emergency messages in the cluster. Comparative analysis between the proposed method and existing methods proves the effectiveness of our method with minimum transmission delay and reduced routing control overhead.

Reconfigurable hardware architecture of public key crypto processor for VANET and wireless sensor nodes

This work proposes encryption of text and image data, embedding as elliptic curve point. Finite field arithmetic is utilised efficiently in this reconfigurable crypto system. Pre-computations for text data and image input conversion is done using MATLAB. This architecture is tailored for cryptographic applications and VANET using Xilinx Spartan-xc3s100e-4-fg320 FPGA with Verilog coding. Total encryption and decryption time results around 10.09021 microseconds for 100×100 images, 22.091 microseconds for 256×256 images and 0.029 microseconds for a message. The message size is varied with different stream size and dynamic mapping of input data and a cipher image with high randomness indicates good security i.e., less vulnerable to attacks. An entropy statistical analysis is performed on plain and encrypted images to assess the strength of the proposed method. An encryption throughput rate is 450 Mbps and area throughput 3.63, which is a good improvement over previous implementations.

Reconfigurable hardware architecture of public key crypto processor for VANET and wireless sensor nodes

This work proposes encryption of text and image data, embedding as elliptic curve point. Finite field arithmetic is utilised efficiently in this reconfigurable crypto system. Pre-computations for text data and image input conversion is done using MATLAB. This architecture is tailored for cryptographic applications and VANET using Xilinx Spartan-xc3s100e-4-fg320 FPGA with Verilog coding. Total encryption and decryption time results around 10.09021 microseconds for 100×100 images, 22.091 microseconds for 256×256 images and 0.029 microseconds for a message. The message size is varied with different stream size and dynamic mapping of input data and a cipher image with high randomness indicates good security i.e., less vulnerable to attacks. An entropy statistical analysis is performed on plain and encrypted images to assess the strength of the proposed method. An encryption throughput rate is 450 Mbps and area throughput 3.63, which is a good improvement over previous implementations.

MAR_Worm: Secure and Efficient Wormhole Detection Scheme through Trusted Neighbour Nodes in VANETs

VANET is an application and subclass of MANET’s, in which nodes are mobiles and considered as moving, communicating vehicles in a wireless adhoc network. Vehicles communicate through dedicated short rage communication (DSRC) via IEEE 802.11p protocol. With the progress of wireless technology, vehicular ad hoc network has become emerging technology to support real-time traffic condition, safety, entertainment, enhance driver experience and emergency navigation in intelligent transport system (ITS). Core of VANETs application is the communication between vehicle to vehicle (V2V), vehicle to roadside unit (V2RSU) and securing the data messages from malicious activities and attackers in the network. Securing V2V and V2RSU communication has raised challenging issues in detecting and avoiding malicious attackers for secure communications. VANET’s are exposed to different threats while routing data, wormhole attack is the most threatening routing attack which severely effects VANET routing data and causes incorrect routing by private tunnels and damages to VANET’s communication in terms of data leakage, data dropping, and delayed delivery. However existing attack detection schemes have failed to meet secured VANETs communication leading to packet loss. In this paper we propose an efficient wormhole detection mechanism by creating potential and trusted neighbour nodes discovery (TNND) in VANETs, which can detect malicious nodes through enabling common forwarding neighbour nodes as witness to monitor data packets are forwarded by malicious nodes. Basically this mechanism is based on trust management. This scheme is resilient and resistant against attackers launching malicious nodes to corrupt entire network. Simulation is carried on event driven network simulator and results shows efficient detection of wormhole nodes, increases packet delivery and performs better than existing detection scheme.

Malicious Node Detection using Route Prediction based on HMM

Driving route prediction methods based on Hidden Markov Model accurately predicts a vehicle’s entire route throughout a trip. Trip history of driver alone cannot be used for predicting the route. Routine history of routes can be modelled and learned for predicting purposes. Driver behavior, another factor of route prediction can be considered as another factor of route prediction. Route recommendation mechanism helps to identify the probability of mobility of vehicles over time. This method can be extended to identify malicious nodes within network traffic. First we define a road network model, the driving routes in a hexagonal coordinate system, build HMM models to predict the movement using a method of training set based on K-means++ technique. The route predicted is taken as input and transmitted along with network data using encrypted headers. A method to identify malicious nodes in VANETs using HMM of prediction about routes helps to identify malicious message from a compromised node. One method of identifying suspicious message is the signal strength which is incompatible with its originator's geographical position. We provide encrypted headers in protocols for detecting suspicious transmissions. Identified malicious node information is disseminated in the network. Evaluation of the detection rate and the efficiency of solution is analyzed using cryptographic methods based on cloud computing. This helps to identify the malicious nodes in the network traffic.

Vanet: A Comparative Study Of Topology Based Routing Protocols

It is an important and an interesting research paper in which we will study the different protocols their working paths, areas, limitations their connectivity to each other regarding VANET. As we know that VANET can be viewed as a subset of MANET; vehicles are used as mobile nodes in VANET. In VANET, each vehicle is considered as a node. In VANET, vehicles are connected to each other or to roadside units through wireless media which creates a wide range network. These vehicles act as mobile nodes that enable handoffs i.e. vehicles can drop out of the network by move out of the signal range.

Swarm Intelligence based efficient routing algorithm for platooning in VANET through Ant Colony Optimization

Today’s era is of smart technology, Computing intelligence and simulations. Many areas are now fully depended on simulation results for implementing real time workflow. Worldwide researchers and many automobile consortium are working to make intelligent Vehicular Ad hoc Network but till yet it is just a theory-based permutation. If we take VANET routing procedures then it is mainly focussing on AODV, DSDV and DSR routing protocols. Similarly, one more area of Swarm Intelligence is also attained attention of industry and researchers. Due the behavior of dynamic movement of vehicle and ants, Ant Colony Optimization is best suited for VANET performance simulations. Much of the work has already done and in progress for routing protocols in VANET but not focused on platooning techniques of vehicle nodes in VANET. In our research idea, we came up with a hypothesis that proposes efficient routing algorithm that made platooning in VANET optimized by minimizing the average delay waiting and stoppage time. In our methodology, we have used OMNET++, SUMO, Veins and Traci for testing of our hypothesis. Parameters that we took into consideration are end-to-end delay as an average, packet data delivery ratio, throughput, data packet size, number of vehicle nodes etc. Swarm Intelligence has proved a way forward in VANET scenarios and simulation for more accurate results. In this paper, we implemented Ant Colony Optimization technique in VANET simulation and proved through results that if it integrates with VANET routing scenarios then result will be at its best.

Approach for Detection of Malicious Nodes in VANET

In order to ensure the users security within the vehicle–specific applications Intelligent Transport Systems (ITS) are designed. For avoiding any kind of loss there is a communication between the users for exchanging important data. Related to the Vehicle Transportation there are several applications of the ITS. There is a requirement for which there is an introduction of Ad hoc Networks (VANETs) for enhancing the safety and efficiency of ground transportation networks and real time information which is its main purpose.

A Survey of Vehicular ad Hoc Network Routing Protocols

Vehicular Ad-hoc Network (VANET) is an emerging autonomous dynamic topology network. It is a special kind of Mobile Ad-hoc Network in which the vehicles exchange their information with each other. VANET turns every car in it into a mobile node and use these nodes to create a mobile dynamic network. The purpose of VANET is to supply a wireless connectivity and deploy various applications such as collision avoidance, safety and improving the traffic efficiency as provisioned by the Intelligent Transportation System (ITS). The vehicles are constrained by the realistic traffic environment, and now the simulations are mainly network simulations which cannot simulate the real trace of the vehicle. But as nodes in VANETS have very high mobility, so there are lots of challenges to route the packets to there final destination which need to be addressed by existing/proposing new solutions for the same. Keeping view of above, In this paper, We summarize the existing VANET routing protocols and classify and compare them. Then, We list several classic routing algorithms and analyze their characteristics and advantages and disadvantages. Finally, by analyzing the status quo of vehicle-mounted routing protocols, we illustrate the difficulties and challenges that vehicle-mounted routing protocols will encounter in the future.

A Combined Modified OpportunisticNeighbor Selection and Vehicle Localization Routing Approach for Improved Connectivity in Indian Road Scenario

In the recent years, VANET is becoming a spectacular research area in wireless networks. The high mobility vehicular node in VANET dynamically changes the network topology resulting in highly unstable vehicle connectivity. This induces network partitioning and hence ensuring link availability remains to be a challenging task. To surpass these issues, design of efficient VANET routing algorithms is necessary. The routing design for VANET scenario is highly complex and challenging making the existing AODV, greedy, cluster based routing algorithms to suffer from degraded link quality resulting in high end-to-end delay and significant packet loss. Although Opportunistic Neighbor Selection (ONS) scheme proves to be a better routing logic, it does not seem to always ensure link availability at road intersections, particularly in Indian road scenario, where multi road lane discipline is very hard to implement. To overcome these limitations, a combination of Modified Opportunistic Neighbor Selection (MONS) and Vehicle Localization (VL) routing logic for adoption in Indian road sector has been proposed in this paper. This paper addresses the connectivity challenges and provides better solution to achieve improved performance. In this work, two specific scenarios namely: varied mobility/node density rates is considered by treating the other fixed inorder to evaluate the suitability of the proposed logic in terms of packet delivery ratio, end-to-end delay.

Management of Node in VANET by Shifting The Position of Road Side Units

Management of Node in VANET by Shifting The Position of Road Side Units