Secure Authentication Mechanism for Cluster based Vehicular Adhoc Network (VANET): A Survey

Vehicular Ad Hoc Networks (VANETs) play a crucial role in Intelligent Transportation Systems (ITS) by facilitating communication between vehicles and infrastructure. This communication aims to enhance road safety, improve traffic efficiency, and enhance passenger comfort. The secure and reliable exchange of information is paramount to ensure the integrity and confidentiality of data, while the authentication of vehicles and messages is essential to prevent unauthorized access and malicious activities. This survey paper presents a comprehensive analysis of existing authentication mechanisms proposed for cluster-based VANETs. The strengths, weaknesses, and suitability of these mechanisms for various scenarios are carefully examined. Additionally, the integration of secure key management techniques is discussed to enhance the overall authentication process. Cluster-based VANETs are formed by dividing the network into smaller groups or clusters, with designated cluster heads comprising one or more vehicles. Furthermore, this paper identifies gaps in the existing literature through an exploration of previous surveys. Several schemes based on different methods are critically evaluated, considering factors such as throughput, detection rate, security, packet delivery ratio, and end-to-end delay. To provide optimal solutions for authentication in cluster-based VANETs, this paper highlights AI- and ML-based routing-based schemes. These approaches leverage artificial intelligence and machine learning techniques to enhance authentication within the cluster-based VANET network. Finally, this paper explores the open research challenges that exist in the realm of authentication for cluster-based Vehicular Adhoc Networks, shedding light on areas that require further investigation and development

Fixed Cluster Based Cluster Head Selection Algorithm in Vehicular Adhoc Network

The emergence of Vehicular Adhoc Networks (VANETs) is expected support variety of applications for driver assistance, traffic efficiency and road safety. For proper transmission of messages in VANET, one of the proposed solutions is dividing the network into clusters and then selecting a cluster head (CH) in each cluster. This can decrease the communication overhead between road side units (RSUs) and other components of VANETs, because instead of every node communicating with RSU, only CH communicates with RSU and relays relevant messages. In clustering, an important step is the selection of CH. In this thesis, we implemented vehicle to vehicle (V2V), cluster head to road side unit and road side unit to trusted authority authentication for the clustered network. We also presented a heuristic algorithm for selecting a suitable vehicle as the cluster head in a cluster. For the selection of head vehicle, we used weighted fitness values based on three parameters; trust value, position from the cluster boundary and absolute relative average speed. Simulation results indicate that the proposed approach can lead to improvements in terms of QoS metrics like delay, throughput and packet delivery ratio

Secure Message Dissemination with QoS Guaranteed Routing in Internet of Vehicles

Internet of Vehicles (IoV) is a variant of vehicular adhoc network (VANET) where vehicles can communicate with other vehicles, infrastructure devices, parking lots and even pedestrians.  Communication to other entities is facilitates through various services like DSRC, C2C-CC. Fake messages can be propagated by attackers for various selfish needs. Complex authentication procedures can affect the propagation of emergency messages. Thus a light weight mechanism to ensure the trust of messages without affecting the delivery deadlines for emergency messages. Addressing this problem, this work proposes a clustering based network topology for IoV where routing is optimized for message dissemination of various classes using hybrid meta-heuristics.  In addition, two stage message authentication technique combining collaborative authentication with Bayesian filtering is proposed to verify the authenticity of message. Through simulation analysis, the proposed solution is found to detect fake messages with an accuracy of 96% with 10% lower processing delay compared to existing works

State-of-the-art authentication and verification schemes in VANETs:A survey

Vehicular Ad-Hoc Networks (VANETs), a subset of Mobile Ad-Hoc Networks (MANETs), are wireless networks formed around moving vehicles, enabling communication between vehicles, roadside infrastructure, and servers. With the rise of autonomous and connected vehicles, security concerns surrounding VANETs have grown. VANETs still face challenges related to privacy with full-scale deployment due to a lack of user trust. Critical factors shaping VANETs include their dynamic topology and high mobility characteristics. Authentication protocols emerge as the cornerstone of enabling the secure transmission of entities within a VANET. Despite concerted efforts, there remains a need to incorporate verification approaches for refining authentication protocols. Formal verification constitutes a mathematical approach enabling developers to validate protocols and rectify design errors with precision. Therefore, this review focuses on authentication protocols as a pivotal element for securing entity transmission within VANETs. It presents a comparative analysis of existing protocols, identifies research gaps, and introduces a novel framework that incorporates formal verification and threat modeling. The review considers key factors influencing security, sheds light on ongoing challenges, and emphasises the significance of user trust. The proposed framework not only enhances VANET security but also contributes to the growing field of formal verification in the automotive domain. As the outcomes of this study, several research gaps, challenges, and future research directions are identified. These insights would offer valuable guidance for researchers to establish secure authentication communication within VANETs

Secure Data Aggregation in Vehicular-Adhoc Networks: A Survey

AbstractVehicular ad hoc networks (VANETs) are an upcoming technology that is gaining momentum in recent years. That may be the reason that the network attracts more and more attention from both industry and academia. Due to the limited bandwidth of wireless communication medium, scalability is a major problem. Data aggregation is a solution to this. The goal of data aggregation is to combine the messages and disseminate this in larger region. While doing aggregation integrity of the information can not be easily verified and attacks may be possible. Hence aggregation must be secure. Although there are several surveys covering VANETs, they do not concentrate on security issues specifically on data aggregation. In this paper, we discuss and analyse various data aggregation techniques and their solutions

Analysis of Black hole Attack in Ad hoc On-Demand Distance Vector (AODV) Routing Protocol : Vehicular Ad-hoc Networks (VANET) Context

In past years, popularity of Mobile Ad hoc Networks has led to the conception of Vehicular Ad hoc Networks. These networks must be highly secure before their implementation in real world. One of the vital aspects of these networks is routing protocol. Most of the protocols in VANET acknowledge all nodes in a network to be genuine by default. But there might be malicious nodes which can make the network vulnerable to various attacks. One such attacks is a black hole attack on AODV routing protocol. Because of its popularity, AODV and black hole attack are taken into consideration for this thesis. The aim of the thesis is to analyze effects of black hole attack on AODV and understand security need of routing protocols in VANET. The experimentation for this thesis was performed with 40, 60 and 80 nodes in network simulator (NS). The performance metrics such as average throughput, end to end delay and packet delivery ratio of each assumed scenarios under blackhole attack and with prevention method are calculated. The obtained calculations are compared to analyze the network performance of AODV. The results from the simulator demonstrate that overall network performance of AODV increased with black hole prevention algorithm in comparison to AODV under black hole attack only. Out of all the performance metrics that are used to analyze the network performance, the average throughput of AODV is significantly increased by 21 percent (approximately) when the mitigation algorithm is applied. The prevention approach used for the thesis can make AODV perform better against black hole attack. However, this approach is limited to a small to medium sized networks only