Vehicular Ad Hoc Networks Research Articles

A hybrid CNN-GRU-based intrusion detection system for secure communication in vehicular adhoc network

ABSTRACT Vehicular Ad hoc Network (VANET) is a component of the Intelligent Transportation System (ITS) which furnishes communication among vehicles. It delivers comfort and safety information to passengers and vehicle drivers. Security plays a vital role during the transmission of data as the various distinct security attacks directly influence the safety of the passengers on the road. Several security attacks will disrupt normal functions like the transmission of data. Some security breaches inject false information which affects the safety of drivers. However, there are several demurrers in detecting abnormal activities efficiently as the traditional system faces imbalanced data problems. This paper presents an Intrusion Detection System (IDS) for detecting anomalies and protecting communication systems from several distinct attacks. The proposed IDS utilizes two deep learning (DL) mechanisms such as Convolutional Neural Network (CNN) and Gated Recurrent Unit (GRU) for detecting anomalies in the vehicular network. The hybrid CNN-GRU mechanism helps in solving the overfitting and low-velocity problems. It also detects several attacks and protects the ad hoc network from those attacks to safeguard the vehicle users. The results show that the propounded model outperforms the other traditional detection mechanisms by 10.79% in terms of performance compared to other IDS.

A Privacy-Preserving V2I Fast Authentication Scheme in VANETs

Due to the characteristics of high-speed movement of vehicles, authentication between vehicles and roadside units (RSUs) needs to be performed quickly. Vehicles can obtain the authentication information of the relevant RSUs from the certification authority (CA) in advance through route planning. Fast authentication can be performed when the vehicle enters the RSU range. However, in most of the current vehicle-to-infrastructure (V2I) fast authentication schemes, when the vehicle requests the authentication information of an RSU from the CA, the vehicle often needs to provide the CA with the travel path information, which leads to the CA easily obtaining the travel path of the vehicle. In addition, the CA encrypts the private keys of RSUs and sends them to vehicles as authentication keys, and the vehicles can obtain the private key information of RSUs directly after decryption. Once the private keys of RSUs are leaked, vehicular ad hoc networks (VANETs) can be attacked by malicious access. In order to protect the confidentiality of RSU private keys and the route privacy of vehicles, we propose a privacy-preserving V2I fast authentication scheme in VANETs. The scheme realizes the confidentiality of RSU private keys and the route privacy protection of vehicles by improving the oblivious transfer (OT) algorithm. Security analysis proves that our scheme has good privacy and attack resistance. Finally, performance evaluation shows that the proposed scheme performs better in terms of computational overhead and communication overhead compared to related schemes.

CPPA-RORS: A conditional privacy-preserving authentication scheme based on revocable one-time ring signature for VANETs

Vehicular ad-hoc networks (VANETs) are a wireless communication system designed to improve driving safety and traffic management, with a focus on enhancing road traffic efficiency and safety. Privacy protection is one of the crucial security challenges for VANETs. However, considering the high mobility of vehicles that frequently transmit delay-intolerant safety and informative messages, two problems exist in some ring signature-based conditional privacy-preserving authentication (CPPA) schemes for VANETs: first, vehicles cannot detect the malicious vehicles when a malicious vehicle signs a message multiple times; and second, the TAs cannot reveal vehicles’ identities when some vehicles engage in illegal activities. To address these concerns, we propose a CPPA scheme based on revocable one-time ring signature (CPPA-RORS) scheme, leveraging the properties of ring signatures. The scheme ensures anonymity of the honest vehicles while providing TAs with the ability to reveal malicious vehicles at any time. We allow one vehicle only can sign one signature on one message, called one-time, to safeguard vehicle privacy with high security. CPPA-RORS scheme provides the formal security model for VANETs, and in particular simultaneously offers message-linkability and mandatory revocability, effectively preventing the double-spending attack (Shrestha et al. 2020) and enabling TAs to revoke the anonymity of any vehicle at any time for further enhancing the security and trustworthiness of the networks. Theoretical analysis and experimental results show that CPPA-RORS provides robust security measures and privacy for vehicles in VANETs.

Position Falsification Detection Approach Using Travel Distance-Based Feature

Abstract This paper addresses the vulnerability of vehicular ad hoc networks (VANETs) to malicious attacks, specifically focusing on position falsification attacks. Detecting misbehaving vehicles in VANETs is challenging due to the dynamic nature of the network topology and vehicle mobility. The paper considers five types (constant attack, constant offset attack, random attack, random offset attack, and eventually stop attack) of position falsification attacks with varying traffic and attack densities, considered the most severe attacks in VANETs. To improve the detection of these attacks, a novel travel distance feature and an enhanced two-stage detection approach are proposed for classifying position falsification attacks in VANETs. The approach involves deploying the misbehavior detection system within roadside units (RSUs) by offloading computational work from vehicles (onboard units, or OBUs) to RSUs. The performance of the proposed approach was evaluated against different classifiers, including a wide range of paradigms (KNN, Decision Tree, and Random Forest), using the VeReMi dataset. Experimental results indicate that the proposed method based on Random Forest achieved an accuracy of 99.9% and an F1-Score of 99.9%, which are better not only than those achieved by KNN and Decision Tree but also than the most recent approaches in the literature survey.

PFCAS—Paring free certificate less aggregate scheme for ensuring efficient authentication in vehicular Ad-hoc networks

PFCAS—Paring free certificate less aggregate scheme for ensuring efficient authentication in vehicular Ad-hoc networks

Efficient and secure routing with UAV: GuidedPheromone update based on improved Ant colony optimization and fuzzy logic for congestion control in vehicular ad-hoc network

Efficient and secure routing with UAV: GuidedPheromone update based on improved Ant colony optimization and fuzzy logic for congestion control in vehicular ad-hoc network

Automatic house location identification using location service based VANET

SummaryThe vehicular ad hoc network (VANET) provides a variety of applications and is gaining popularity due to the reuse of network resources. Exact location identification with optimum delay is the demand of all vehicle users. Currently, individuals are utilizing the Global Positioning System (GPS) to ascertain the precise geographical coordinates of a given location. The drawback of GPS technology is its inability to accurately determine location and use GPS in some remote areas. Searching for the location of a particular house randomly incurs a loss of fuel as well as increases delay. This motivates us to propose one automated method through VANET using location service‐based routing for the location identification of a house. The proposed work involves searching for the location of a house using the open‐source MongoDB database, and the operations on the database are performed using the tool Node‐Red. By simulation using SUMO and Network Simulator 2.35, the proposed work is evaluated and compared with existing location service‐based routing like geographic location service (GLS) and hierarchical location service (HLS). The proposed work performs better in terms of routing efficiency (end‐to‐end latency, packet delivery rate), location efficiency (request sends, query success rate, and request travel time), and routing and location overhead (MAC bandwidth consumption). Also, the performance of the proposed work is presented as stable by increasing the number of vehicles. The statistical analysis of the packet delivery ratio and CBR end‐to‐end latency is carried out using T score.

QoS-based energy-efficient hybrid routing protocols in RSU assisted VANET using clustering mechanism

ABSTRACT Vehicular ad hoc networks (VANET) communication framework are employed to improve communication between vehicles on the highway and urban roads. Evaluating the best routing path by satisfying the QoS (Quality of Service) plays a substantial role in networking. Researchers for maximising the routing efficiency have employed numerous methods. But these criteria cannot be attained effectively due to certain limitations, including frequent route failure, high overhead, increased packet loss rate, less throughput and packet delivery rate. Hence, this work presents an effective strategy to offer better communication services with less energy consumption and high flexibility using QoS-based energy efficient routing framework with clustering (QoS_EErcF) network model. Initially, different clusters are formed by considering the constraints like node direction, link reliability, speed and distance. The cluster heads (CH) are chosen from the clusters with the dissemination of gateway nodes and cluster members using an Amended rapid cosine similarity-founded clustering mechanism (Arc_SimC). The best routing strategy for transmitting the data from source to destination is performed by using Integrated Pelican with grasshopper optimisation algorithm (IPel_Ghop). Constraints such as bandwidth, node distance, energy, packet loss rate, network traffic and end-to-end delay are considered to find the optimal path. The results are simulated using MATLAB, whereas the energy efficiency of a proposed model is obtained to be 98.37%, and the packet delivery ratio is attained as 99.60%.

A lossless quantization approach for physical-layer key generation in vehicular ad hoc networks based on received signal strength

Vehicular Ad Hoc Networks (VANETs) provide various benefits and play a crucial role in improving efficiency and ensuring human safety across different applications. However, these advantages also give rise to security challenges and privacy concerns, necessitating a thorough examination of security attacks. Current key generation schemes, particularly those based on the Physical-Layer Model (PLM), face limitations such as low key generation rates and inadequate randomness. This paper introduces an innovative key generation method that utilizes adaptive physical-layer techniques and lossless quantization. The method involves an eight-level quantization process, which enables precise granularity and adaptive selection of quantization thresholds to tailor the computation of Received Signal Strength (RSS) measurements to individual needs. The adaptive approach ensures the retention of information within RSS measurements, resulting in reduced bit disagreement rates and enhanced randomness of the generated keys. Simulated evaluations demonstrate the effectiveness of the proposed method, showing superior performance in terms of bit generation, entropy, and secrecy rates, while also minimizing the occurrence of unnecessary measurements. This advancement holds significant promise for strengthening the security framework within VANETs.

Discharging driven energy sharing protocol for V2V communication in vehicular energy networks

With the growing concern over range anxiety among electric vehicle (EV) owners due to limited battery capacity and sparse charging infrastructure, EV-to-EV (V2V) energy sharing emerges as a crucial solution to extend driving range. Leveraging the vehicular energy network (VEN) enabled by dynamic wireless power transfer (DWPT) technology, energy sharing among EVs in motion becomes feasible. However, the effective establishment of communication and identification of suitable V2V energy sharing pairs pose significant challenges, particularly for EVs with discharging demands. To address this challenge, we propose a new discharging driven energy sharing protocol based on vehicular ad-hoc networks (VANETs). Firstly, we present a routing approach for transmitting discharging information through VANETs, considering key factors such as distance, state of charge, number of neighbor vehicles, and vehicle speed. This routing scheme facilitates efficient relay node selection on road segments and intersections, ensuring optimal communication paths. Subsequently, we formulate a charging requester selection model to identify the most suitable requester for energy sharing. This model optimizes individual utility while accounting for the state of charge of the requesters, ensuring a comprehensive and inclusive approach to V2V energy sharing. Finally, we develop an acknowledgment message transmission scheme to ensure the completion of selection acknowledgment between discharging EVs and charging EVs. This scheme includes provisions for recovery in case of forwarding link failures, ensuring robust communication in dynamic vehicular environments. Extensive simulations conducted using network simulator 2 (NS-2) demonstrate the superior performance of the proposed protocol in terms of packet delivery ratio, end-to-end delay, and overall V2V energy sharing efficiency.

A Data Dissemination Algorithm Based on Maximization of Causal Path Entropy in Vehicular Ad Hoc Networks

A Data Dissemination Algorithm Based on Maximization of Causal Path Entropy in Vehicular Ad Hoc Networks

Privacy-preserving authentication approach for vehicular networks

Vehicle AdHoc networks have an important role in intelligent transport systems that enhance safety in road usage by transmitting real traffic updates in terms of congestion and road accidents. The dynamic nature of the vehicular AdHoc networks make them susceptible to attacks because once malicious users gain access to the network they can transform traffic data. It is essential to protect the vehicular ad hoc network because any attack can cause unwanted harm, to solve this it is important to have an approach that detects malicious vehicles and not give them access to the network. The proposed approach is a privacy preserving authentication approach that authenticates vehicles before they have access to the vehicular network thereby identifying malicious vehicles. The model was executed in docker container that simulates the network in a Linux environment running Ubuntu 20.04. The model enhances privacy by assigning Pseudo IDs to authenticated vehicles and the results demonstrate effectiveness of the solution in that unlike other models it boasts faster authentication and lower computational overhead which is necessary in a vehicular network scenario.

Comparative analysis of reactive routing protocols for vehicular adhoc network communications

In the recent past, vehicular adhoc networks (VANETs) have gained a lot of importance. The routing protocols play a vital role to deliver payloads from one vehicle to another one while they are moving at relative speeds. It is a challenging task to select a routing protocol for VANETs because of the uneven distribution and high mobility of vehicles. In this paper, we have analysed the two standard reactive protocols, adhoc on-demand distance vector (AODV) and ant colony optimization (ACO). The performance comparison of AODV and ACO routing protocols has been presented in this paper. The results show AODV performed better in terms of energy consumption and routing overhead. While considering the throughput, energy loss ratio, and delay ACO has performed. ACO resulted as upperhand.

SL-PPCP: Secure and Low-Cost Privacy-Preserving Communication Protocol for Vehicular Ad Hoc Networks

SL-PPCP: Secure and Low-Cost Privacy-Preserving Communication Protocol for Vehicular Ad Hoc Networks

Efficient Authentication Steps for Vehicle Transmission in Ad-Hoc Networks

Vehicular ad-hoc networks (VANETs) are underactive development, thanks in part to recent advances in wireless communication and networking technologies. The most fundamental part of VANET is to enable message authentications between vehicles and roadside units. Message authentication using proxy vehicles has been proposed to reduce the computational overhead of roadside units significantly. In this message authentication scheme, a proxy vehicle that verifies multiple messages at the same time improves roadside units’ efficiency. In this paper first, we show that the only proxy-based authentication scheme (PBAS) presented for this goal by Liu et al. cannot guarantee message authenticity and also it is not resistant to impersonation and modification attacks and false acceptance of batched invalid signatures. Next, we propose a new identity-based message authentication scheme using proxy vehicles (ID-MAP). Then guarantee that it can satisfy the message authentication requirements, existential unforgeability of underlying signatures against adaptability chosen message, and identity attack is proved under the Elliptic Curve discrete logarithm problem (ECDLP) in the random oracle model. It should be highlighted that ID MAP not only is more efficient than PBAS since it is pairing-free and identity based and also it does not use map-to-point hash functions, also, it satisfies the security and privacy requirements of VANETs. Furthermore, analysis shows that the required time to verify 3000 messages in ID-MAP is reduced by 76% compared to that PBAS.

An Integrated DQN and RF Packet Routing Framework for the V2X Network

With the development of artificial intelligence technology, deep reinforcement learning (DRL) has become a major approach to the design of intelligent vehicle-to-everything (V2X) routing protocols for vehicular ad hoc networks (VANETs). However, if the V2X routing protocol does not consider both real-time traffic conditions and historical vehicle trajectory information, the source vehicle may not transfer its packet to the correct relay vehicles and, finally, to the destination. Thus, this kind of routing protocol fails to guarantee successful packet delivery. Using the greater network flexibility and scalability of the software-defined network (SDN) architecture, this study designs a two-phase integrated DQN and RF Packet Routing Framework (IDRF) that combines the deep Q-learning network (DQN) and random forest (RF) approaches. First, the IDRF offline phase corrects the vehicle’s historical trajectory information using the vehicle trajectory continuity algorithm and trains the DQN model. Then, the IDRF real-time phase judges whether vehicles can meet each other and makes a real-time routing decision to select the most appropriate relay vehicle after adding real-time vehicles to the VANET. In this way, the IDRF can obtain the packet transfer path with the shortest end-to-end delay. Compared to two DQN-based approaches, i.e., TDRL-RP and VRDRT, and traditional VANET routing algorithms, the IDRF exhibits significant performance improvements for both sparse and congested periods during intensive simulations of the historical GPS trajectories of 10,357 taxis within Beijing city. Performance improvements in the average packet delivery ratio, end-to-end delay, and overhead ratio of the IDRF over TDRL-RP and VRDRT under different numbers of pairs and transmission ranges are at least 3.56%, 12.73%, and 5.14% and 6.06%, 11.84%, and 7.08%, respectively.

Reduction Jammer Detection and Recovery Algorithms for DSRC Safety Application in VANET

Intelligent Transportation Systems (ITS) encompasses technologies, services, and applications facilitating communication between vehicles (V2V) and between vehicles and fixed infrastructure (V2I and I2V). This mutual interaction constitutes a Vehicular Ad-Hoc Network (VANET) which supports a plethora of applications targeting critical transportation aspects, such as safety, mobility, and environmental considerations. Dedicated Short Range Communications (DSRC), operating on the 5.9 GHz band, is pivotal for such exchanges. We introduced an innovative algorithm designed to identify jamming attacks and transition the Safety Application to a secure fail-safe mode. This algorithm leverages a dual-metric strategy, incorporating both distance and PDR measurements. Field tests confirm that our algorithm adeptly recognizes the activities of deceptive jammers, ensuring a prompt shift of the safety application into its fail-safe state. This paper delves into these countermeasures, evaluating their efficiency via mathematical modeling, simulations, and on-ground testing. Findings acknowledge that these strategies bolster the reliability of safety applications in jamming scenarios. Furthermore, the approaches propounded align with ongoing standardization endeavors by relevant authorities, ensuring communication mediums remain unhindered.

Cryptography-based location privacy protection in the Internet of Vehicles

The evolution of the Internet of Things paradigm in recent years demonstrate a significant impact on the transportation sector, leading to the emergence of a new research field, known as the Internet of Vehicles (IoV). In the IoV, vehicles can exchange information with each other and with the roadside units making use of Vehicular Ad Hoc Networks (VANETs). As this technology reaches near-to-market maturity levels, several issues arise related to the protection of users’ privacy, while the interest of adversaries for such private user data in IoV environments gets stronger. This paper aims to present a review of the state-of-the-art techniques tackling the protection of location privacy in IoV environments, as well as experimental evaluation findings regarding the usage of various cryptographic algorithms for the protection of information exchange in these networks. In the conducted evaluations, the AES algorithm has been used as the main standard, which has been coupled with several other encryption/decryption algorithms, such as RSA, ECC and NTRU. The metrics used for the evaluation include measurements over the key generation process, the certificate generation, the encryption/decryption times, the signature generation/verification times, etc. Moreover, the size of messages in the negotiation, the pseudonym exchange and the new pseudonym enabling phases has been recorded, while the energy consumption in the exchange pseudonyms phase has also been measured. All previous experiments have been carried out mainly on NS-3 and SUMO open-source software aiming to have an estimation of how the aforementioned algorithms behave under constrained resources such as CPU usage and power.

Provably secure optimal homomorphic signcryption for satellite-based internet of things

Satellites have long been reliable and widely used mediums for communication. With recent advancements in the Internet of Things (IoT), satellite-based IoT has emerged, enhancing global connectivity by enabling real-time communication between remote sensing devices and central hubs through satellite links. However, secure and authenticated communication between Low Earth Orbit (LEO) satellites and resource-constrained ground devices remains underexplored. This paper introduces a novel homomorphic signcryption scheme designed for satellite IoT environments. Our scheme employs hyperelliptic curve cryptography and homomorphic encryption to facilitate the privacy-preserving transmission of aggregated data from multiple IoT devices to LEO satellites. We benchmark our homomorphic signcryption scheme against several established schemes tailored for different network environments, including for satellite networks, Identity-based Signcryption for Smart Grids, 3-Factor Authentication schemes and heterogeneous Vehicular Ad-hoc Networks (VANETs) encryption schemes. Our scheme demonstrates substantial improvements in computational efficiency, communication overhead, and storage capacity. It reduces computational costs by 90% to 99%, communication overhead by 41% to 92%, and storage demands by 62% to 93% compared to existing methods. These quantitative findings demonstrate the practical viability of our approach for satellite IoT deployments with limited resources. Additionally, the robustness of our approach is confirmed through formal security validation using BAN Logic and Scyther, which verifies its strong security, optimal performance, and privacy preservation capabilities, making it ideally suited for real-world satellite IoT systems.

Enhancement of VANETS Security against Gray Hole Attack with ANFIS-GWO and LBK

Vehicular Ad Hoc Networks (VANETs) have emerged as a critical component of intelligent transportation systems, facilitating real time communication among vehicles and infrastructure. However, the open and dynamic nature of VANETs makes them vulnerable to various security threats, among which gray hole attacks pose significant challenges. In gray hole attacks, malicious nodes manipulate or selectively drop data packets, disrupting communication and compromising network integrity. In response to these challenges, this paper proposes an innovative approach that integrates the Adaptive Neuro Fuzzy Inference System (ANFIS) with Grey Wolf Optimization (GWO). The main objective of this research is to develop a robust ANFIS GWO framework capable of identifying and mitigating gray hole attacks in real time VANET scenarios. Through extensive simulations and experiments, the performance of proposed technique in terms of average energy consumed, throughput, Packet Delivery Ratio (PDR) and packet drop is examined. The results demonstrate that the ANFIS GWO approach not only improves the resilience of VANETs against gray hole attacks but also guarantees reliable and secure communication among vehicles and infrastructure.