Security In Vehicular Ad Hoc Networks Research Articles

Enhancing Black Hole Attack Detection in VANETs: A Hybrid Approach Integrating DBSCAN Clustering with Decision Trees

Ensuring the security of communication is crucial in Vehicular Ad Hoc Networks (VANETs) to protect the integrity of information sharing among cars. To implement VANET communication as an answer for the different uses, secure communication is necessary. The unreliability of VANET environments is caused by message delays or tampering in VANET applications. Finding the sweet spot between VANET security and performance and dependability is the primary goal. This project’s overarching goal is to fortify VANETs against Blackhole Routing Attacks and, by identifying and blocking harmful nodes, to mitigate the blackhole impact. This paper proposes a robust hybrid approach for the detection of black hole attacks in VANETs, leveraging the synergy between DBSCAN (Density-Based Spatial Clustering of Applications with Noise) clustering and Decision Trees. DBSCAN, a density-based clustering algorithm, is employed to identify spatial clusters of vehicles, while Decision Trees are utilized to discern normal communication patterns from malicious ones within these clusters. The integration of these two techniques enhances the accuracy and efficiency of black hole attack detection in the dynamic and resource-constrained VANET environment. Experimental results demonstrate the effectiveness of the proposed hybrid approach, providing a promising solution for bolstering the security of VANETs against emerging threats. Here in result 73.89% improvement is received in Packet Drop Rate using DBSCAN, also minor improvement over Throughput and Average end to end delay and major improvement in terms of Network Routing Load.

Enhancing Security and Performance in Vehicular Adhoc Networks: A Machine Learning Approach to Combat Adversarial Attacks

Integrating Machine Learning (ML) techniques into Vehicular Adhoc Networks (VANETs) provides promising features in autonomous driving and ITS applications. In this paper, DSRC data is used to evaluate the effectiveness of different ML models, including Naive Bayes, Random Forest, KNN, and Gradient Boosting, in normal and adversarial scenarios. Since the dataset is relatively imbalanced, the Synthetic Minority Over-sampling Technique (SMOTE) is employed for sampling, and defensive distillation for improving model resilience to adversarial perturbations. From the results, it is clear that models such as Gradient Boosting and Random Forest show high accuracy in both cases, thus showing the potential of using Machine Learning to improve VANET security and reliability when new threats appear. Through this research, the significance of the application of ML in the protection of vehicular communication in order to enhance both traffic safety and flow has been articulated.

An efficient model of enhanced optimization and dilated-GRU based secured multi-access edge computing with blockchain for VANET sector

The establishment of Vehicular Ad Hoc Networks (VANETs) has brought significant advantages to humans, yet it also raises crucial safety considerations. Security is one of the major challenges in VANETs and is receiving significant attention. Hostile Onboard Units (OBUs) can use a variety of tactics including blocking, monitoring and tampering to harm neighboring OBUs to make illicit profits. The widespread use of the decentralized architecture built around blockchain technology has enabled the clear, safe, and dispersed storage and transmission of VANET application-related information without the need for an administrative center of authority. Perhaps the most important parts of the blockchain-driven VANET system involve implementing an efficient and adaptable consensus system, which remains an open academic issue. The objective of the suggested solution is to create a deep learning model for blockchain that will guarantee VANET security. This network topology is comprised of three layers: “perception, edge computing, and services”. The initial layer that comprises the blockchain operation is employed to demonstrate the privacy of VANET information. Additionally, cloud-based services as well as edge computing are used by the perception layer. The data is safeguarded by the service layer through the application of the blockchain system and storage in the cloud. The last layer aids in meeting user criteria for throughput and QoS. The main objective of this model is to evaluate the reliability of vehicle nodes maintained on the blockchain. Here, the node authentication is handled by an Adaptive Dilated Gated Recurrent Unit (AD-GRU), where the hyper-parameters of the recommended AD-GRU model are optimally tuned by an Enhanced Osprey Optimization Algorithm (EOOA). Finally, the proposed system is simulated and its extensive results are carried out. In contrast with other approaches, the novel system delivers the superior results of securing the data over the VANET environment.

Unlinkable and Revocable Signcryption Scheme for VANETs

Vehicular ad-hoc networks (VANETs) can significantly improve the level of urban traffic management. However, the sender unlinkability has become an intricate issue in the field of VANETs’ encryption. As the sender signcrypts a message, the receiver has to use the sender’s identity or public key to decrypt it. Consequently, the sender can be traced using the same identity or public key, which poses some security risks to the sender. To address this issue, we present an unlinkable and revocable signcryption scheme (URSCS), where an efficient and powerful signcryption mechanism is adopted for communication. The sender constructs a polynomial to generate a unique session key for each communication, which is then transmitted to a group of receivers, enabling the same secret message to be sent to multiple receivers. Each time a secret message is sent, a new key pair is generated, and an anonymization mechanism is introduced to conceal the true identity of the vehicle, thus preventing malicious attackers from tracing the sender through the public key or the real identity. With the introduction of the identification public key, this scheme supports either multiple receivers or a single receiver, where the receiver can be either road side units (RSUs) or vehicles. Additionally, a complete revocation mechanism is constructed with extremely low communication overhead, utilizing the Chinese remainder theorem (CRT). Formal and informal security analyses demonstrate that our URSCS scheme meets the expected security and privacy requirements of VANETs. The performance analysis shows that our URSCS scheme outperforms other represented schemes.

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.

IPCAS: An improved conditional privacy-preserving certificateless aggregate signature scheme without bilinear pairing for VANETs

Recently, Gong et al. proposed a Certificateless Aggregate Signature (CLAS) scheme (shorted by PCAS) with conditional privacy-preserving without bilinear pairing for Vehicular Ad-hoc Networks (VANETs). Unfortunately, after analyzing security, the PCAS scheme fails to satisfy the necessary unlinkability in VANETs and is vulnerable to the public key replacement forgery attack of the Type-I adversary. Subsequently, this article analyzes the causes of these two security issues in detail and proposes an improved CLAS scheme for VANETs (called IPCAS). Through security analysis, this article proves that the IPCAS is existentially unforgeable under the adaptive chosen message attacks against Type-I and Type-II adversaries in the random oracle model, and satisfies the necessary security and privacy requirements in VANETs, including unlinkability. Finally, the performance analysis results show that compared to PCAS for single message and n aggregate messages (n=1000), the computational overhead of IPCAS is reduced by 20.01% and 49.08% respectively, and the communication overhead is reduced by 18.75% and 28.14% respectively. Therefore, IPCAS not only makes up for the security vulnerabilities of PCAS but also has better performance.

IoT-Driven solutions for VANET trustworthiness: Examining misconduct and position security challenges

Vehicular ad hoc networks (VANETs) improve the traffic management and road safety by exchanging real-time data between automobiles and roadside infrastructure. Reliable Intelligent Transport Systems (ITS) solutions tend to boost VANET data security, integrity and dependability. These systems communicate VANET data between infrastructure and automobiles using sensors, Internet of Things (IoT) devices and communication technologies. IoT-driven includes a Real-Time Traffic Observation optimizes VANET route design. Traffic management and safety improve with ITS-connected cars and infrastructure. Remote communication technologies enhance traffic management and decision-making by sending a real-time data between cars and infrastructure. Smart parking systems use real-time parking availability data from IoT sensors and devices to maximize space use and reduce congestion. Security and misbehavior are dependable problems in 40 IoT-driven VANET studies. Miscommunication and unstandardized are the main security issues which pose hazards. This review shows VANETs that requires authentication, encryption and anomaly detection to prevent attacks and IoT for transportation sector. This extensive review covers VANET reliability and IoT-driven real-time traffic monitoring, ITS, remote communication and intelligent parking systems. This review analyzes the metrics to assess the many detection techniques which includes, misconduct-Aware On-Demand Collaborative Intrusion Detection System (MACIDS) and Collision-Induced Dissociation Spectroscopy (CIDS), (i) Accuracy (ii) False Positive Rate, (iii) precision, (iv) recall (v) False Negative Rate and (vi) F1-Score in VANET security in Attack Detection Rates (ADR), misbehavior detection, evaluation metrics and detection algorithms were studied using CIC-IDS data. Due to misconduct and security issues, a strong IoT-driven solutions are required to improve VANET trustworthiness and offers a secure and reliable vehicular communication networks for safer and more efficient transportation systems.

Vehicular ad-hoc security improvements using decentralised consensus blockchain

For safer roads, a more efficient driving experience, and protection against attackers, the intelligent cars communicate with one another or with the roadside unit (RSU). The fundamental security requirements of Vehicular Ad-hoc Networks (VANETs) must be nonrepudiable, genuine, and incorporate these three. Additionally, protecting against attackers should be done in particular specific situations. However, the VANET's main disadvantages are its centralized design and the absence of procedures for ensuring confidentiality and privacy. In this paper, proposed decentralised consensus blockchain architecture for VANET that uses blockchain technology to address these problems. The VANET no longer needs a central authority or third-party administration thanks to the introduction of the blockchain. In order to ensure data integrity and accelerate up system processing, the hash value of the pseudonyms will be recorded on the blockchain. By eliminating trust difficulties between the entities, this effectively addresses challenges that arise in centralised designs. The suggested method for VANETs security. Experimental investigation demonstrates that the provided architecture outperforms the available options in terms of security enhancement.

A quantum-secure certificateless aggregate signature protocol for vehicular ad hoc networks

Vehicular ad hoc networks (VANETs) have revolutionized communication between vehicles and infrastructure, notably enhancing traffic management and passenger safety. However, VANETs are vulnerable to security threats, especially regarding data authenticity. Aggregate signature is a powerful technique that reduces computational and communication burdens by aggregating multiple signatures from different signers into a single signature. Traditional aggregate signature schemes, based on large prime number decomposition and the discrete logarithm problem, cannot effectively resist quantum attacks. This paper introduces a novel quantum secure certificateless aggregate signature (QSCLAS) scheme designed to enhance data security and privacy in VANETs. Our proposed scheme employs the number theory research unit (NTRU) algorithm. As a lattice-based cryptographic algorithm, NTRU is renowned for its security against quantum computer attacks, making it an essential component of our quantum-secure solution. By eliminating the need for expensive bilinear pairing operations, our proposed scheme achieves high efficiency and practicality in resource-limited VANETs environments. The security analysis demonstrates our scheme's resilience against both Type-I and Type-II adversaries in the random oracle model under the small integer solution (SIS) problem on the NTRU lattice. Furthermore, compared with existing approaches, the results illustrate that our proposed scheme offers significant advantages in signature generation and verification cost, as well as lower transmission overhead than other lattice-based schemes, thereby making it highly suitable for VANETs environments.

Cryptanalysis of Two Conditional Privacy Preserving Authentication Schemes for Vehicular Ad Hoc Networks

Conditional Privacy Preserving Authentication (CPPA) schemes are an effective way of securing communications in vehicular ad hoc networks (VANETs), as well as ensuring user privacy and accountability. Cryptanalysis plays a crucial role in pointing out the vulnerabilities in existing schemes to enable the development of more resilient ones. In 2019, Zhang proposed a CPPA scheme for VANET security (PA-CRT), based on identity batch verification (IBV) and Chinese Remainder Theorem (CRT). In this paper, we cryptanalyze Zhang’s scheme and point out its vulnerability to impersonation and repudiation attacks. In 2023, Zhang’s scheme was cryptanalyzed by Tao; however, we point out flaws in Tao’s cryptanalysis due to invalid assumptions; hence, we propose countermeasures to Tao’s attacks. Furthermore, in 2021, Xiong proposed a Certificateless Aggregate Signature (CLAS) scheme which is also cryptanalyzed in this paper. Finally, we analyze the causes and countermeasures by pointing out the vulnerabilities in each scheme that enabled us to launch successful attacks and proposing changes that would fortify these schemes against similar attacks in the future.

Efficient Routing Algorithm Towards the Security of Vehicular Ad-Hoc Network and Its Applications

Efficient Routing Algorithm Towards the Security of Vehicular Ad-Hoc Network and Its Applications

Digital Twin for Transportation Big Data: A Reinforcement Learning-Based Network Traffic Prediction Approach

Vehicular Ad-Hoc Networks (VANETs), as the crucial support of Intelligent Transportation Systems (ITS), have received great attention in recent years. With the rapid development of VANETs, various services have generated a great deal of data that can be used for transportation planning and safe driving. Especially, with the advent of Coronavirus Disease 2019 (COVID-19), the transportation system has been impacted, thus novel modes of transportation planning and intelligent applications are necessary. Digital twins can provide powerful support for artificial intelligence applications in Transportation Big Data (TBD). The features of VANETs are varying, which arises the main challenge of digital twins applying in TBD. Network traffic prediction, as part of digital twins, is useful for network management and security in VANETs, such as network planning and anomaly detection. This paper proposes a network traffic prediction algorithm aiming at time-varying traffic flows with a large number of fluctuations. This algorithm combines Deep Q-Learning (DQN) and Generative Adversarial Networks (GAN) for network traffic feature extraction. DQN is leveraged to carry out network traffic prediction, in which GAN is involved to represent Q-network. Meanwhile, the generative network can increase the number of samples to improve the prediction error. We evaluate the performance of our method by implementing it on three real network traffic data sets. Finally, we compare the two state-of-the-art competing methods with our method.

A Reliable Physical Layer Key Generation Scheme Based on RSS and LSTM Network in VANET

With the rapid development of information and communication technology, Vehicular AD hoc Networks (VANET) has attracted more and more attention. In order to provide traffic safety services, vehicles frequently share information related to road traffic, such as vehicle motion data and traffic flow data. Reliable key generation is the basis of VANET security system construction. At present, most key generation schemes rely on a trusted third-party, so there are security risks. Traditional key agreement protocols have high overhead, and is not suitable for the latency-sensitive requirements of VANET. The physical layer security technology extracts the fingerprint of the wireless channel and the identity of the device, and generates the key quickly and in real time without the third party distribution. A physical layer key generation scheme based on Received Signal Strength (RSS) is proposed to realize Vehicle-to-Vehicle (V2V) secure communications. Firstly, a network model based on Long Short-Term Memory (LSTM) network and Kalman Filtering is proposed to effectively enhance the reciprocity of physical layer information in dynamic environment. Secondly, a lossless quantization scheme is proposed, which achieves a lower bit disagreement rate and a higher bit generation rate. Thirdly, the inconsistent bits are corrected by fuzzy extractor, the confidentiality of the key exchange process is enhanced by zero knowledge proof, and the security of the key is improved by using hash function for privacy amplification. Finally, the experimental results show that the proposed scheme has great improvements in data correlation, bit disagreement rate, bit generation rate and bit distribution randomness.

Privacy and security issues surrounding vehicular Adhoc networks

Vehicular Ad-Hoc Networks (VANETs) is a type of mobile ad hoc network (MANET) specifically designed for communication among vehicles on the road. VANETs enable vehicles to communicate with each other and with roadside infrastructure, forming a dynamic and self-organizing network without the need for a fixed communication infrastructure. Security concerns in VANETs encompass a range of threats, including Authentication and Authorization attacks, Sybil attacks, Denial-of-Service incidents, Location spoofing, and Eavesdropping. Privacy, on the other hand, is a paramount concern in VANETs due to the sensitive nature of location-based data, Identity Disclosure, and user consent Control. The paper emphasizes the necessity for robust security mechanisms and outlines specific requirements for safeguarding VANETs. Proposed mitigation measures, including cryptographic techniques and authentication mechanisms, are critically assessed for their effectiveness and feasibility. The findings provide a comprehensive understanding of the complexities surrounding privacy and security in VANETs, contributing valuable insights for the development of resilient and privacy-preserving vehicular communication systems.

Sustainable and Round-Optimized Group Authenticated Key Exchange in Vehicle Communication

Vehicle authentication is an essential component validating the vehicle’s identity and ensuring the integrity of transformed data for intelligent transport vehicles (ITS) in the vehicular ad hoc network (VANET). Easy to deploy and operate privacy-enhancing vehicle authentication mechanisms are the mainstay for the widespread ITS in the VANET. Very recently, VANET security architectures are constituting by IEEE 1609.2 group, NoW project, the SeVeCom project. However, these approaches heavily depend on the consuming public key infrastructure (PKI) and certification authorities (CA). In this work, walking along the research line, we attempt to design authentication protocols with two diverse factors for Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) networks, respectively, without depending on the stumbling block PKI/CA. In addition, a smooth projective hash function (SPHF) (a.k.a., a special case of the designated-verifier zero-knowledge proof system) guarantees any recipient can confirm the authenticity and integrity of the received messages without knowing the authentication factors. Thus, to optimize the communication round, SPHF is used to design a (group) two-factor authenticated key exchange (AKE) with low-interactive communication rounds. The proof-of-concept implementation indicates that the computation and communication overheads introduced by our solution are acceptable in real-world deployments. The security of the proposed approach is validated using Bellare-Pointcheval-Rogaway (BPR) model along with the experimental evaluation and the theoretical analysis.

Augmenting Vehicular Ad Hoc Network Security and Efficiency with Blockchain: A Probabilistic Identification and Malicious Node Mitigation Strategy

This manuscript delineates the development of an avant garde dual-layer blockchain architecture, which has been meticulously engineered to augment the security and operational efficacy of vehicular ad hoc networks (VANETs). VANETs, which are integral to the infrastructure of intelligent transport systems, facilitate the critical exchange of information between vehicular nodes. Despite their significance, these networks confront an array of formidable security vulnerabilities. Our innovative approach, employing a dual blockchain framework—the event chain and the reputation chain—meticulously tracks network activities, thereby significantly enhancing the trustworthiness and integrity of the system. This research presents a transformative dual-layer blockchain architecture, which was conceived to address the intricate security challenges pervasive in VANETs. The architecture pivots on a sophisticated reputation assessment framework, thus leveraging the principles of Bayesian inference and the analytical rigor of historical data to markedly diminish observational errors, as well as elevate the accuracy of reputation evaluations for vehicular nodes. A salient feature of our methodology is the implementation of an attenuation factor, which has been deftly calibrated to modulate the impact of historical behaviors on current reputation scores, thereby ensuring their relevance and alignment with recent vehicular interactions. Additionally, the numerical threshold serves as an indispensable mechanism, thus establishing a definitive criterion for the early identification of potentially malicious activities and enabling the activation of proactive security measures to safeguard the network’s integrity. Empirical validation of our dual-layer blockchain model has yielded a remarkable 86% efficacy in counteracting malevolent behaviors, thus significantly outperforming extant paradigms. These empirical outcomes underscore the model’s potential as a vanguard in the domain of secure and efficient reputation management within VANETs, thereby heralding a substantial advancement in the sphere of intelligent transportation systems.

A Novel Secure Routing Design Based on Physical Layer Security in Millimeter-Wave VANET

With the continuous development of millimeter-wave communication technology, new requirements such as ultra-reliability and higher data rates pose new challenges to the security issues of traditional cryptographic encryption in vehicular ad hoc networks (VANET). Physical layer security uses the characteristics of different wireless channels to protect the information security. In this paper, we propose a novel VANET routing mechanism that utilizes physical layer security to improve the secrecy performance, which is compatible with the millimeter-wave vehicular network. Specifically, we design a new secure routing selection factor, the utility function, that takes into account the effects of both secrecy rate and single-hop transmission distance to achieve the hop selection. In addition, we propose a novel routing mechanism and design a waiting mechanism based on the utility function. Compared with the traditional routing algorithms, the greedy perimeter stateless routing (GPSR) and Dijkstra simulation results illustrate that our design achieves superior performance in secrecy performance and dynamic adaptability.

Trust based multi objective honey badger algorithm to secure routing in vehicular ad-hoc networks

<span lang="EN-US">A vehicular ad-hoc network (VANET) is a set of intelligent vehicles that interact without any fixed infrastructure. Data transmission between each transmitter/receiver pair is accomplished using routing protocols. However, communication over the VANET is vulnerable to malicious attacks, because of the unavailability of fixed infrastructure and wireless communication. In this paper, the trust based multi objective honey badger algorithm (TMOHBA) is proposed to achieve secure routing over the VANET. The TMOHBA is optimized by incorporating different cost functions, namely, trust, end to end delay (EED), routing overhead, energy, and distance. The developed secure route discovery using the TMOHBA is used to improve the robustness against the malicious attacks, for increasing the data delivery. Moreover, the shortest path discovery is used to minimize the delay while improving the security of VANET. The TMOHBA method is evaluated using the packet delivery ratio (PDR), throughput and EED. Existing researches such as hybrid enhanced glowworm swarm optimization (HEGSO) and ad-hoc on-demand distance vector based secure protocol (AODV-SP) are used to evaluate the TMOHBA method. The PDR of the TMOHBA method for 10 malicious attacks is 90.6446% which is higher when compared to the HEGSO and AODV-SP.</span>

CascadMLIDS: A Cascaded Machine Learning Framework for Intrusion Detection System in VANET

Vehicular ad hoc networks (VANETs) incorporating vehicles as an active and fast topology are gaining popularity as wireless communication means in intelligent transportation systems (ITSs). The cybersecurity issue in VANETs has drawn attention due to the potential security threats these networks face. An effective cybersecurity measure is essential as security threats impact the overall system, from business disruptions to data corruption, theft, exposure, and unauthorized network access. Intrusion detection systems (IDSs) are popular cybersecurity measures that detect intrusive behavior in a network. Recently, the machine learning (ML)-based IDS has emerged as a new research direction in VANET security. ML-based IDS studies have focused on improving accuracy as a typical classification task without focusing on malicious data. This study proposes a novel IDS for VANETs that offers more attention to classifying attack cases correctly with minimal features required by applying principal component analysis. The proposed Cascaded ML framework recognizes the difference between the attack and normal cases in the first step and classifies the attack data in the second step. The framework emphasizes that an attack should not be classified into the normal class. Finally, the proposed framework is implemented with an artificial neural network, the most popular ML model, and evaluated with the Car Hacking dataset. In addition, the study also investigates the efficiency of typical classification tasks and compares them with results of the proposed framework. Experimental results on the Car Hacking dataset have revealed the proposed method to be an effective IDS and that it outperformed the existing state-of-the-art ML models.

Inspecting VANET with Various Critical Aspects – A Systematic Review

Due to its strategic significance in the area of smart transportation to facilitate Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication, Vehicular Ad Hoc Networks (VANETs) have grown very popular in recent years. The rapid increase in the number of vehicles on the road has also led to the development of heterogeneous, large-scale, and highly dynamic VANETs, which introduce difficulty to fulfill the stringent requirements, which include low latency, high mobility, top security, and massive connectivity of the 5G network. Research works in VANETs mainly focus on message transmission within strict delay requirements based on different applications, data privacy and security. In this respect, a number of studies have been carried out by the researchers that propose models and solutions linked to the enhancement of VANET from several aspects, including applications, Quality of Service (QoS), security, physical layer fading, Artificial Intelligence (AI) techniques, Medium Access Control (MAC), and routing protocols. These factors serve as the driving force for this study's thorough examination of VANETs, which includes information on specific applications, QoS, channel fading, MAC protocols, channel access mechanisms, routing protocols, security, and difficulties. None of the surveys in existence today address all critical aspects of VANET in a single survey. In this paper, a complete taxonomy of VANETs has been provided based on various issues. First, an overview of VANET is presented with different applications. Then, QoS in VANETs and different proposed MAC protocols are discussed. Channel fading and access mechanisms are presented. After that, routing protocols, security, and clustering in VANETs are provided. AI approaches proposed in VANET are also summarized. Finally, a discussion of future research direction for all aspects is presented. This article might be used as a guide or a point of reference while designing and creating applications, networking and communication systems, and data security for VANETs.