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Laouiti, Dhia Eddine, Ayaida, Marwane, Messai, Nadhir, Najeh, Sameh, Najjar, Leila, Chaabane, Ferdaous.  2022.  Sybil Attack Detection in VANETs using an AdaBoost Classifier. 2022 International Wireless Communications and Mobile Computing (IWCMC). :217–222.
Smart cities are a wide range of projects made to facilitate the problems of everyday life and ensure security. Our interest focuses only on the Intelligent Transport System (ITS) that takes care of the transportation issues using the Vehicular Ad-Hoc Network (VANET) paradigm as its base. VANETs are a promising technology for autonomous driving that provides many benefits to the user conveniences to improve road safety and driving comfort. VANET is a promising technology for autonomous driving that provides many benefits to the user's conveniences by improving road safety and driving comfort. The problem with such rapid development is the continuously increasing digital threats. Among all these threats, we will target the Sybil attack since it has been proved to be one of the most dangerous attacks in VANETs. It allows the attacker to generate multiple forged identities to disseminate numerous false messages, disrupt safety-related services, or misuse the systems. In addition, Machine Learning (ML) is showing a significant influence on classification problems, thus we propose a behavior-based classification algorithm that is tested on the provided VeReMi dataset coupled with various machine learning techniques for comparison. The simulation results prove the ability of our proposed mechanism to detect the Sybil attack in VANETs.
Zhao, Jing, Wang, Ruwu.  2022.  FedMix: A Sybil Attack Detection System Considering Cross-layer Information Fusion and Privacy Protection. 2022 19th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON). :199–207.
Sybil attack is one of the most dangerous internal attacks in Vehicular Ad Hoc Network (VANET). It affects the function of the VANET network by maliciously claiming or stealing multiple identity propagation error messages. In order to prevent VANET from Sybil attacks, many solutions have been proposed. However, the existing solutions are specific to the physical or application layer's single-level data and lack research on cross-layer information fusion detection. Moreover, these schemes involve a large number of sensitive data access and transmission, do not consider users' privacy, and can also bring a severe communication burden, which will make these schemes unable to be actually implemented. In this context, this paper introduces FedMix, the first federated Sybil attack detection system that considers cross-layer information fusion and provides privacy protection. The system can integrate VANET physical layer data and application layer data for joint analyses simultaneously. The data resides locally in the vehicle for local training. Then, the central agency only aggregates the generated model and finally distributes it to the vehicles for attack detection. This process does not involve transmitting and accessing any vehicle's original data. Meanwhile, we also designed a new model aggregation algorithm called SFedAvg to solve the problems of unbalanced vehicle data quality and low aggregation efficiency. Experiments show that FedMix can provide an intelligent model with equivalent performance under the premise of privacy protection and significantly reduce communication overhead, compared with the traditional centralized training attack detection model. In addition, the SFedAvg algorithm and cross-layer information fusion bring better aggregation efficiency and detection performance, respectively.
Yang, Haonan, Zhong, Yongchao, Yang, Bo, Yang, Yiyu, Xu, Zifeng, Wang, Longjuan, Zhang, Yuqing.  2022.  An Overview of Sybil Attack Detection Mechanisms in VFC. 2022 52nd Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W). :117–122.
Vehicular Fog Computing (VFC) has been proposed to address the security and response time issues of Vehicular Ad Hoc Networks (VANETs) in latency-sensitive vehicular network environments, due to the frequent interactions that VANETs need to have with cloud servers. However, the anonymity protection mechanism in VFC may cause the attacker to launch Sybil attacks by fabricating or creating multiple pseudonyms to spread false information in the network, which poses a severe security threat to the vehicle driving. Therefore, in this paper, we summarize different types of Sybil attack detection mechanisms in VFC for the first time, and provide a comprehensive comparison of these schemes. In addition, we also summarize the possible impacts of different types of Sybil attacks on VFC. Finally, we summarize challenges and prospects of future research on Sybil attack detection mechanisms in VFC.
Sharan, Bhagwati, Chhabra, Megha, Sagar, Anil Kumar.  2022.  State-of-the-art: Data Dissemination Techniques in Vehicular Ad-hoc Networks. 2022 9th International Conference on Computing for Sustainable Global Development (INDIACom). :126—131.
Vehicular Ad-hoc Networks (VANETs) is a very fast emerging research area these days due to their contribution in designing Intelligent transportation systems (ITS). ITS is a well-organized group of wireless networks. It is a derived class of Mobile Ad-hoc Networks (MANETs). VANET is an instant-formed ad-hoc network, due to the mobility of vehicles on the road. The goal of using ITS is to enhance road safety, driving comfort, and traffic effectiveness by alerting the drivers at right time about upcoming dangerous situations, traffic jams, road diverted, weather conditions, real-time news, and entertainment. We can consider Vehicular communication as an enabler for future driverless cars. For these all above applications, it is necessary to make a threat-free environment to establish secure, fast, and efficient communication in VANETs. In this paper, we had discussed the overviews, characteristics, securities, applications, and various data dissemination techniques in VANET.
M, Gayathri, Gomathy, C..  2022.  Fuzzy based Trusted Communication in Vehicular Ad hoc Network. 2022 2nd International Conference on Intelligent Technologies (CONIT). :1—4.
Vehicular Ad hoc Network (VANET) is an emerging technology that is used to provide communication between vehicle users. VANET provides communication between one vehicle node to another vehicle node, vehicle to the roadside unit, vehicle to pedestrian, and even vehicle to rail users. Communication between nodes should be very secure and confidential, Since VANET communicates through wireless mode, a malicious node may enter inside the communication zone to hack, inject false messages, and interrupt the communication. A strong protocol is necessary to detect malicious nodes and authenticate the VANET user to protect them from malicious attacks. In this paper, a fuzzy-based trust authentication scheme is used to detect malicious nodes with the Mamdani fuzzy Inference system. The parameter estimation, rules have been framed using MATLAB Mamdani Fuzzy Inference system to select a genuine node for data transmission.
Tariq, Usman.  2022.  Security-Aware Malicious Event Detection using Multivariate Deep Regression Setup for Vehicular Ad hoc Network Aimed at Autonomous Transportation System. 2022 International Conference on Wireless Communications Signal Processing and Networking (WiSPNET). :354—358.
Vehicular Ad-hoc Networks (VANET) are capable of offering inter and intra-vehicle wireless communication among mobility aware computing systems. Nodes are linked by applying concepts of mobile ad hoc networks. VANET uses cases empower vehicles to link to the network to aggregate and process messages in real-time. The proposed paper addresses a security vulnerability known as Sybil attack, in which numerous fake nodes broadcast false data to the neighboring nodes. In VANET, mobile nodes continuously change their network topology and exchange location sensor-generated data in real time. The basis of the presented technique is source testing that permits the scalable identification of Sybil nodes, without necessitating any pre-configuration, which was conceptualized from a comparative analysis of preceding research in the literature.
Yassin, Ahmed Mohsen, Azer, Marianne A..  2022.  Performance Comparison of AODV and DSDV In Vehicular Ad Hoc Networks. 2022 2nd International Mobile, Intelligent, and Ubiquitous Computing Conference (MIUCC). :402—405.
Vehicle Ad-Hoc Networks (VANETs) are a special type of Mobile Ad-Hoc Network (MANETs). In VANETs, a group of vehicles communicates with each other to transfer data without a need for a fixed infrastructure. In this paper, we compare the performance of two routing protocols: Ad-hoc on Demand Distance Vector protocol (AODV) and Destination-Sequenced Distance Vector protocol (DSDV) in VANETs. We measure the reliability of each protocol in the packet delivery.
Choudhary, Swapna, Dorle, Sanjay.  2021.  Empirical investigation of VANET-based security models from a statistical perspective. 2021 International Conference on Computational Intelligence and Computing Applications (ICCICA). :1—8.
Vehicular ad-hoc networks (VANETs) are one of the most stochastic networks in terms of node movement patterns. Due to the high speed of vehicles, nodes form temporary clusters and shift between clusters rapidly, which limits the usable computational complexity for quality of service (QoS) and security enhancements. Hence, VANETs are one of the most insecure networks and are prone to various attacks like Masquerading, Distributed Denial of Service (DDoS) etc. Various algorithms have been proposed to safeguard VANETs against these attacks, which vary concerning security and QoS performance. These algorithms include linear rule-checking models, software-defined network (SDN) rules, blockchain-based models, etc. Due to such a wide variety of model availability, it becomes difficult for VANET designers to select the most optimum security framework for the network deployment. To reduce the complexity of this selection, the paper reviews statistically investigate a wide variety of modern VANET-based security models. These models are compared in terms of security, computational complexity, application and cost of deployment, etc. which will assist network designers to select the most optimum models for their application. Moreover, the paper also recommends various improvements that can be applied to the reviewed models, to further optimize their performance.
Cabelin, Joe Diether, Alpano, Paul Vincent, Pedrasa, Jhoanna Rhodette.  2021.  SVM-based Detection of False Data Injection in Intelligent Transportation System. 2021 International Conference on Information Networking (ICOIN). :279—284.
Vehicular Ad-Hoc Network (VANET) is a subcategory of Intelligent Transportation Systems (ITS) that allows vehicles to communicate with other vehicles and static roadside infrastructure. However, the integration of cyber and physical systems introduce many possible points of attack that make VANET vulnerable to cyber attacks. In this paper, we implemented a machine learning-based intrusion detection system that identifies False Data Injection (FDI) attacks on a vehicular network. A co-simulation framework between MATLAB and NS-3 is used to simulate the system. The intrusion detection system is installed in every vehicle and processes the information obtained from the packets sent by other vehicles. The packet is classified into either trusted or malicious using Support Vector Machines (SVM). The comparison of the performance of the system is evaluated in different scenarios using the following metrics: classification rate, attack detection rate, false positive rate, and detection speed. Simulation results show that the SVM-based IDS is able to provide high accuracy detection, low false positive rate, consequently improving the traffic congestion in the simulated highway.
Perarasi, T., Vidhya, S., Moses M., Leeban, Ramya, P..  2020.  Malicious Vehicles Identifying and Trust Management Algorithm for Enhance the Security in 5G-VANET. 2020 Second International Conference on Inventive Research in Computing Applications (ICIRCA). :269—275.
In this fifth generation of vehicular communication, the security against various malicious attacks are achieved by using malicious vehicles identification and trust management (MAT) algorithm. Basically, the proposed MAT algorithm performs in two dimensions, they are (i) Node trust and (ii) information trust accompanied with a digital signature and hash chain concept. In node trust, the MAT algorithm introduces the special form of key exchanging algorithm to every members of public group key, and later the vehicles with same target location are formed into cluster. The public group key is common for each participant but everyone maintain their own private key to produce the secret key. The proposed MAT algorithm, convert the secrete key into some unique form that allows the CMs (cluster members) to decipher that secrete key by utilizing their own private key. This key exchanging algorithm is useful to prevent the various attacks, like impersonate attack, man in middle attack, etc. In information trust, the MAT algorithm assigns some special nodes (it has common distance from both vehicles) for monitoring the message forwarding activities as well as routing behavior at particular time. This scheme is useful to predict an exact intruder and after time out the special node has dropped all the information. The proposed MAT algorithm accurately evaluates the trustworthiness of each node as well as information to control different attacks and become efficient for improving a group lifetime, stability of cluster, and vehicles that are located on their target place at correct time.
Aman, Muhammad Naveed, Sikdar, Biplab.  2021.  AI Based Algorithm-Hardware Separation for IoV Security. 2021 IEEE Globecom Workshops (GC Wkshps). :1–6.
The Internet of vehicles is emerging as an exciting application to improve safety and providing better services in the form of active road signs, pay-as-you-go insurance, electronic toll, and fleet management. Internet connected vehicles are exposed to new attack vectors in the form of cyber threats and with the increasing trend of cyber attacks, the success of autonomous vehicles depends on their security. Existing techniques for IoV security are based on the un-realistic assumption that all the vehicles are equipped with the same hardware (at least in terms of computational capabilities). However, the hardware platforms used by various vehicle manufacturers are highly heterogeneous. Therefore, a security protocol designed for IoVs should be able to detect the computational capabilities of the underlying platform and adjust the security primitives accordingly. To solve this issue, this paper presents a technique for algorithm-hardware separation for IoV security. The proposed technique uses an iterative routine and the corresponding execution time to detect the computational capabilities of a hardware platform using an artificial intelligence based inference engine. The results on three different commonly used micro-controllers show that the proposed technique can effectively detect the type of hardware platform with up to 100% accuracy.
Lin, Hua Yi, Hsieh, Meng-Yen, Li, Kuan-Ching.  2021.  A Multi-level Security Key Management Protocol Based on Dynamic M-tree Structures for Internet of Vehicles. 2021 International Symposium on Performance Evaluation of Computer and Telecommunication Systems (SPECTS). :1–5.
With the gradually popular high-speed wireless networks and 5G environments, the quality and reliability of network services will be suited for mobile vehicles. In addition to communicating information between vehicles, they can also communicate information with surrounding roadside equipment, pedestrians or traffic signs, and thus improve the road safety of passers-by.Recently, various countries have continuously invested in research on autonomous driving and unmanned vehicles. The open communication environment of the Internet of Vehicles in 5G will expose all personal information in the field of wireless networks. This research is based on the consideration of information security and personal data protection. We will focus on how to protect the real-time transmission of information between mobile vehicles to prevent from imbedding or altering important transmission information by unauthorized vehicles, drivers or passers-by participating in communications. Moreover, this research proposes a multi-level security key management agreement based on a dynamic M-tree structure for Internet of Vehicles to achieve flexible and scalable key management on large-scale Internet of Vehicles.
Xu, Qichao, Zhao, Lifeng, Su, Zhou.  2021.  UAV-assisted Abnormal Vehicle Behavior Detection in Internet of Vehicles. 2021 40th Chinese Control Conference (CCC). :7500–7505.
With advantages of low cost, high mobility, and flexible deployment, unmanned aerial vehicle (UAVs) are employed to efficiently detect abnormal vehicle behaviors (AVBs) in the internet of vehicles (IoVs). However, due to limited resources including battery, computing, and communication, UAVs are selfish to work cooperatively. To solve the above problem, in this paper, a game theoretical UAV incentive scheme in IoVs is proposed. Specifically, the abnormal behavior model is first constructed, where three model categories are defined: velocity abnormality, distance abnormality, and overtaking abnormality. Then, the barging pricing framework is designed to model the interactions between UAVs and IoVs, where the transaction prices are determined with the abnormal behavior category detected by UAVs. At last, simulations are conducted to verify the feasibility and effectiveness of our proposed scheme.
Luo, Baiting, Liu, Xiangguo, Zhu, Qi.  2021.  Credibility Enhanced Temporal Graph Convolutional Network Based Sybil Attack Detection On Edge Computing Servers. 2021 IEEE Intelligent Vehicles Symposium (IV). :524—531.
The emerging vehicular edge computing (VEC) technology has the potential to bring revolutionary development to vehicular ad hoc network (VANET). However, the edge computing servers (ECSs) are subjected to a variety of security threats. One of the most dangerous types of security attacks is the Sybil attack, which can create fabricated virtual vehicles (called Sybil vehicles) to significantly overload ECSs' limited computation resources and thus disrupt legitimate vehicles' edge computing applications. In this paper, we present a novel Sybil attack detection system on ECSs that is based on the design of a credibility enhanced temporal graph convolutional network. Our approach can identify the malicious vehicles in a dynamic traffic environment while preserving the legitimate vehicles' privacy, particularly their local position information. We evaluate our proposed approach in the SUMO simulator. The results demonstrate that our proposed detection system can accurately identify most Sybil vehicles while maintaining a low error rate.
Benadla, Sarra, Merad-Boudia, Omar Rafik.  2021.  The Impact of Sybil Attacks on Vehicular Fog Networks. 2021 International Conference on Recent Advances in Mathematics and Informatics (ICRAMI). :1—6.
The Internet of Vehicles (IoV) is a network that considers vehicles as intelligent machines. They interact and communicate with each other to improve the performance and safety of traffic. IoV solves certain problems, but it has some issues such as response time, which prompted researchers to propose the integration of Fog Computing into vehicular networks. In Vehicular Fog Computing (VFC), the services are provided at the edge of the network to increase data rate and reduce response time. However, in order to satisfy network users, the security and privacy of sensitive data should be guaranteed. Using pseudonyms instead of real identities is one of the techniques considered to preserve the privacy of users, however, this can push malicious vehicles to exploit such a process and launch the Sybil attack by creating several pseudonyms in order to perform various malicious activities. In this paper, we describe the Sybil attack effects on VFC networks and compare them to those in conventional networks, as well as identify the various existing methods for detecting this attack and determine if they are applicable to VFC networks.
Shah, Priyanka, Kasbe, Tanmay.  2021.  Detecting Sybil Attack, Black Hole Attack and DoS Attack in VANET Using RSA Algorithm. 2021 Emerging Trends in Industry 4.0 (ETI 4.0). :1—7.
In present scenario features like low-cost, power-efficientand easy-to-implement Wireless Sensor Networks (WSN’s) has become one of growing prospects.though, its security issues have become a popular topic of research nowadays. Specific attacks often experience the security issues as they easily combined with other attacks to destroy the network. In this paper, we discuss about detecting the particular attacks like Sybil, Black-holeand Denial of Service (DoS) attacks on WSNs. These networks are more vulnerable to them. We attempt to investigate the security measures and the applicability of the AODV protocol to detect and manage specific types of network attacks in VANET.The RSA algorithm is proposed here, as it is capable of detecting sensor nodes ormessages transmitted from sensor nodes to the base station and prevents network from being attacked by the source node. It also improves the security mechanism of the AODV protocol. This simulation set up is performed using MATLAB simulation tool
Maria Stephen, Steffie, Jaekel, Arunita.  2021.  Blockchain Based Vehicle Authentication Scheme for Vehicular Ad-hoc Networks. 2021 IEEE Intelligent Vehicles Symposium Workshops (IV Workshops). :1–6.
Vehicular Ad Hoc Network (VANET) is a pervasive network, where vehicles communicate with nearby vehicles and infrastructure nodes, such as Road-side unit (RSU). Information sharing among vehicles is an essential component of an intelligent transportation system (ITS), but security and privacy concerns must be taken into consideration. Security of the network can be improved by granting access only to authenticated vehicles and restricting or revoking access for vehicles involved in misbehavior. In this paper, we present a novel blockchain based approach to authenticate vehicles and notify other vehicles about any unauthorized messages in real time. This helps protect other vehicles in the network from making critical decisions based on false or inaccurate information. In the proposed architecture, vehicles communicate with each other using pseudonyms or pseudo IDs and the Blockchain is used to securely maintain the real identity of all vehicles, which can be linked to the pseudo IDs if needed. The goal is to protect privacy or individual vehicles, while still ensuring accountability in case of misbehavior. The performance of the proposed approach is evaluated for different vehicle and attacker densities, and results demonstrate it has lower authentication delay and communication overhead compared to existing approaches.
Mohammed, Khalid Ayoub, Abdelgader, Abdeldime M.S., Peng, Chen.  2021.  Design of a Fully Automated Adaptive Quantization Technique for Vehicular Communication System Security. 2020 International Conference on Computer, Control, Electrical, and Electronics Engineering (ICCCEEE). :1–6.
Recently, vehicular communications have been the focus of industry, research and development fields. There are many benefits of vehicular communications. It improves traffic management and put derivers in better control of their vehicles. Privacy and security protection are collective accountability in which all parties need to actively engage and collaborate to afford safe and secure communication environments. The primary objective of this paper is to exploit the RSS characteristic of physical layer, in order to generate a secret key that can securely be exchanged between legitimated communication vehicles. In this paper, secret key extraction from wireless channel will be the main focus of the countermeasures against VANET security attacks. The technique produces a high rate of bits stream while drop less amount of information. Information reconciliation is then used to remove dissimilarity of two initially extracted keys, to increase the uncertainty associated to the extracted bits. Five values are defined as quantization thresholds for the captured probes. These values are derived statistically, adaptively and randomly according to the readings obtained from the received signal strength.
Al-shareeda, Mahmood A., Alazzawi, Murtadha A., Anbar, Mohammed, Manickam, Selvakumar, Al-Ani, Ahmed K..  2021.  A Comprehensive Survey on Vehicular Ad Hoc Networks (VANETs). 2021 International Conference on Advanced Computer Applications (ACA). :156–160.
Vehicle Ad-hoc Networks (VANETs) have recently become an active research area. This is because of its important applications in the transportation field in which vehicles have severe position during activities of daily living in persons. In this paper, the basic background of the VANET from the Intelligent Transportation System (ITS), Mobile Ad-hoc Networks (MANETs), VANET standard and VANET characteristics are discussed. Second, the architecture from components and communications of the system are presented. Then, the critical challenges and future perspectives in this field are comprehensively reviewed. This paper could serve as a guide and reference in the design and development of any new techniques for VANETs. Moreover, this paper may help researchers and developers in the selection of the main features of VANET for their goals in one single document.
Hamdi, Mustafa Maad, Yussen, Yuser Anas, Mustafa, Ahmed Shamil.  2021.  Integrity and Authentications for service security in vehicular ad hoc networks (VANETs): A Review. 2021 3rd International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA). :1–7.
A main type of Mobile Ad hoc Networks (MANET) and essential infrastructure to provide a wide range of safety applications to passengers in vehicles (VANET) are established. VANETs are more popular today as they connect to a variety of invisible services. VANET protection is crucial as its potential use must not endanger the safety and privacy of its users. The safety of these VANETs is essential to safe and efficient safety systems and facilities and uncertainty continues and research in this field continues to grow rapidly. We will explain the characteristics and problems of VANETs in this paper. Also, all threats and attacks that affect integrity and authentication in VANETs will be defined. Description of researchers' work was consequently addressed as the table with the problems of the suggested method and objective.
Naqvi, Ila, Chaudhary, Alka, Rana, Ajay.  2021.  Intrusion Detection in VANETs. 2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO). :1–5.
Vehicular Ad hoc Networks commonly abbreviated as VANETs, are an important component of MANET. VANET refers to the group of vehicles that are interlinked to one another through wireless network. Along with technology, comes the threats. Like other wireless networks, VANETs also are vulnerable to various security threats. Security in VANETs is a major issue that attracted many researchers and academicians. One small security breach can cause a big damage in case of VANETs as in this case human lives are involved. Intrusion Detection Systems (IDS) are employed in VANETs in order to detect and identify any malicious activity in the network. The IDS works by analysing the network and detecting any intrusions tried or made in the network so that proper steps could be taken timely to prevent damage from such activities. This paper reviews Intrusion Detection systems, classification of IDS based on various factors and then the architecture of IDS. We then reviewed some of the recent and important intrusion detection research works and then compared them with one another.
Rabari, Jeet, Kumar, Arun Raj P..  2021.  FIFA: Fighting against Interest Flooding Attack in NDN-based VANET. 2021 International Wireless Communications and Mobile Computing (IWCMC). :1539–1544.
A vehicular Ad-hoc network (VANET) allows groups of autonomous or semi-autonomous vehicles to share information and content with each other and infrastructure. Named Data Networking (NDN) is recently proposed as one of the future internet architectures, which allows communication in network-based upon content name. It has originated from Information-centric networking (ICN). NDN-based VANET uses NDN as an underlying communication paradigm. NDN-based VANET suffers from several security attacks, one such attack is the Interest Flooding Attack (IFA) that targets the core forwarding mechanism of NDN-based VANET. This paper focuses on the detection and mitigation of IFA in NDN-based VANET. We proposed a method FIFA to detect and mitigate IFA. Our proposed method is capable of detecting normal IFA as well as a low-rate IFA. Along with that FIFA also ensures non-repudiation in networks. We have compared our proposed method with the existing mechanism to detect and mitigate IFA named IFAMS. Experiment results show that our method detects and mitigates normal IFA and low-rate IFA in the network.
Agarwal, Piyush, Matta, Priya, Sharma, Sachin.  2021.  Comparative Study of Emerging Internet-of-Things in Traffic Management System. 2021 5th International Conference on Trends in Electronics and Informatics (ICOEI). :422–428.
In recent years, the Internet-of-Things (IoT)-based traffic management system (ITMS) has attracted the attention of researchers from different fields, such as the automotive industry, academia and traffic management, due to its ability to enhance road safety and improve traffic efficiency. ITMS uses the Vehicle Ad-hoc Network (VANET) to communicate messages about traffic conditions or the event on the route to ensure the safety of the commuter. ITMS uses wireless communication technology for communication between different devices. Wireless communication has challenges to privacy and security. Challenges such as confidentiality, authentication, integrity, non-repudiation, identity, trust are major concerns of either security or privacy or both. This paper discusses the features of the traffic system, the features of the traffic management system (TMS) and the features of IoT that can be used in TMS with its challenges. Further, this paper analyses the work done in the last few years with the future scope of IoT in the TMS.
Acharya, Abiral, Oluoch, Jared.  2021.  A Dual Approach for Preventing Blackhole Attacks in Vehicular Ad Hoc Networks Using Statistical Techniques and Supervised Machine Learning. 2021 IEEE International Conference on Electro Information Technology (EIT). :230–235.
Vehicular Ad Hoc Networks (VANETs) have the potential to improve road safety and reduce traffic congestion by enhancing sharing of messages about road conditions. Communication in VANETs depends upon a Public Key Infrastructure (PKI) that checks for message confidentiality, integrity, and authentication. One challenge that the PKI infrastructure does not eliminate is the possibility of malicious vehicles mounting a Distributed Denial of Service (DDoS) attack. We present a scheme that combines statistical modeling and machine learning techniques to detect and prevent blackhole attacks in a VANET environment.Simulation results demonstrate that on average, our model produces an Area Under The Curve (ROC) and Receiver Operating Characteristics (AUC) score of 96.78% which is much higher than a no skill ROC AUC score and only 3.22% away from an ideal ROC AUC score. Considering all the performance metrics, we show that the Support Vector Machine (SVM) and Gradient Boosting classifier are more accurate and perform consistently better under various circumstances. Both have an accuracy of over 98%, F1-scores of over 95%, and ROC AUC scores of over 97%. Our scheme is robust and accurate as evidenced by its ability to identify and prevent blackhole attacks. Moreover, the scheme is scalable in that addition of vehicles to the network does not compromise its accuracy and robustness.
Petrenkov, Denis, Agafonov, Anton.  2021.  Anomaly Detection in Vehicle Platoon with Third-Order Consensus Control. 2021 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology (USBEREIT). :0463–0466.
The development of autonomous connected vehicles, in particular, moving as a platoon formation, has received great attention in recent years. The autonomous movement allows to increase the efficiency of the transportation infrastructure usage, reduce the fuel consumption, improve road safety, decrease traffic congestion, and others. To maintain an optimal spacing policy in a platoon formation, it is necessary to exchange information between vehicles. The Vehicular ad hoc Network (VANET) is the key component to establish wireless vehicle-to-vehicle communications. However, vehicular communications can be affected by different security threats. In this paper, we consider the third-order consensus approach as a control strategy for the vehicle platoon. We investigate several types of malicious attacks (spoofing, message falsification) and propose an anomaly detection algorithm that allows us to detect the malicious vehicle and enhance the security of the vehicle platoon. The experimental study of the proposed approach is conducted using Plexe, a vehicular network simulator that permits the realistic simulation of platooning systems.