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2021-03-09
Stępień, K., Poniszewska-Marańda, A..  2020.  Security methods against Black Hole attacks in Vehicular Ad-Hoc Network. 2020 IEEE 19th International Symposium on Network Computing and Applications (NCA). :1–4.
Vehicular Ad-Hoc Networks (VANET) are liable to the Black, Worm and Gray Hole attacks because of the broadcast nature of the wireless medium and a lack of authority standards. Black Hole attack covers the situation when a malicious node uses its routing protocol in order to publicize itself for having the shortest route to the destination node. This aggressive node publicizes its availability of fresh routes regardless of checking its routing table. The consequences of these attacks could lead not only to the broken infrastructure, but could cause hammering people's lives. This paper aims to investigate and compare methods for preventing such types of attacks in a VANET.
Fiade, A., Triadi, A. Yudha, Sulhi, A., Masruroh, S. Ummi, Handayani, V., Suseno, H. Bayu.  2020.  Performance Analysis of Black Hole Attack and Flooding Attack AODV Routing Protocol on VANET (Vehicular Ad-Hoc Network). 2020 8th International Conference on Cyber and IT Service Management (CITSM). :1–5.
Wireless technology is widely used today and is growing rapidly. One of the wireless technologies is VANET where the network can communicate with vehicles (V2V) which can prevent accidents on the road. Energy is also a problem in VANET so it needs to be used efficiently. The presence of malicious nodes or nodes can eliminate and disrupt the process of data communication. The routing protocol used in this study is AODV. The purpose of this study is to analyze the comparison of blackhole attack and flooding attack against energy-efficient AODV on VANET. This research uses simulation methods and several supporting programs such as OpenStreetMap, SUMO, NS2, NAM, and AWK to test the AODV routing protocol. Quality of service (QOS) parameters used in this study are throughput, packet loss, and end to end delay. Energy parameters are also used to examine the energy efficiency used. This study uses the number of variations of nodes consisting of 20 nodes, 40 nodes, 60 nodes, and different network conditions, namely normal network conditions, network conditions with black hole attacks, and network conditions with flooding attacks. The results obtained can be concluded that the highest value of throughput when network conditions are normal, the greatest value of packet loss when there is a black hole attack, the highest end to end delay value and the largest remaining energy when there is a flooding attack.
2021-02-23
Mendiboure, L., Chalouf, M. A., Krief, F..  2020.  A Scalable Blockchain-based Approach for Authentication and Access Control in Software Defined Vehicular Networks. 2020 29th International Conference on Computer Communications and Networks (ICCCN). :1—11.
Software Defined Vehicular Networking (SDVN) could be the future of the vehicular networks, enabling interoperability between heterogeneous networks and mobility management. Thus, the deployment of large SDVN is considered. However, SDVN is facing major security issues, in particular, authentication and access control issues. Indeed, an unauthorized SDN controller could modify the behavior of switches (packet redirection, packet drops) and an unauthorized switch could disrupt the operation of the network (reconnaissance attack, malicious feedback). Due to the SDVN features (decentralization, mobility) and the SDVN requirements (flexibility, scalability), the Blockchain technology appears to be an efficient way to solve these authentication and access control issues. Therefore, many Blockchain-based approaches have already been proposed. However, two key challenges have not been addressed: authentication and access control for SDN controllers and high scalability for the underlying Blockchain network. That is why in this paper we propose an innovative and scalable architecture, based on a set of interconnected Blockchain sub-networks. Moreover, an efficient access control mechanism and a cross-sub-networks authentication/revocation mechanism are proposed for all SDVN devices (vehicles, roadside equipment, SDN controllers). To demonstrate the benefits of our approach, its performances are compared with existing solutions in terms of throughput, latency, CPU usage and read/write access to the Blockchain ledger. In addition, we determine an optimal number of Blockchain sub-networks according to different parameters such as the number of certificates to store and the number of requests to process.
Olowononi, F. O., Rawat, D. B., Liu, C..  2020.  Dependable Adaptive Mobility in Vehicular Networks for Resilient Mobile Cyber Physical Systems. 2020 IEEE International Conference on Communications Workshops (ICC Workshops). :1—6.

Improved safety, high mobility and environmental concerns in transportation systems across the world and the corresponding developments in information and communication technologies continue to drive attention towards Intelligent Transportation Systems (ITS). This is evident in advanced driver-assistance systems such as lane departure warning, adaptive cruise control and collision avoidance. However, in connected and autonomous vehicles, the efficient functionality of these applications depends largely on the ability of a vehicle to accurately predict it operating parameters such as location and speed. The ability to predict the immediate future/next location (or speed) of a vehicle or its ability to predict neighbors help in guaranteeing integrity, availability and accountability, thus boosting safety and resiliency of the Vehicular Network for Mobile Cyber Physical Systems (VCPS). In this paper, we proposed a secure movement-prediction for connected vehicles by using Kalman filter. Specifically, Kalman filter predicts the locations and speeds of individual vehicles with reference to already observed and known information such posted legal speed limit, geographic/road location, direction etc. The aim is to achieve resilience through the predicted and exchanged information between connected moving vehicles in an adaptive manner. By being able to predict their future locations, the following vehicle is able to adjust its position more accurately to avoid collision and to ensure optimal information exchange among vehicles.

2021-01-28
Javed, M. U., Jamal, A., Javaid, N., Haider, N., Imran, M..  2020.  Conditional Anonymity enabled Blockchain-based Ad Dissemination in Vehicular Ad-hoc Network. 2020 International Wireless Communications and Mobile Computing (IWCMC). :2149—2153.

Advertisement sharing in vehicular network through vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication is a fascinating in-vehicle service for advertisers and the users due to multiple reasons. It enable advertisers to promote their product or services in the region of their interest. Also the users get to receive more relevant ads. Usually, users tend to contribute in dissemination of ads if their privacy is preserved and if some incentive is provided. Recent researches have focused on enabling both of the parameters for the users by developing fair incentive mechanism which preserves privacy by using Zero-Knowledge Proof of Knowledge (ZKPoK) (Ming et al., 2019). However, the anonymity provided by ZKPoK can introduce internal attacker scenarios in the network due to which authenticated users can disseminate fake ads in the network without payment. As the existing scheme uses certificate-less cryptography, due to which malicious users cannot be removed from the network. In order to resolve these challenges, we employed conditional anonymity and introduced Monitoring Authority (MA) in the system. In our proposed scheme, the pseudonyms are assigned to the vehicles while their real identities are stored in Certification Authority (CA) in encrypted form. The pseudonyms are updated after a pre-defined time threshold to prevent behavioural privacy leakage. We performed security and performance analysis to show the efficiency of our proposed system.

2021-01-25
Marasco, E. O., Quaglia, F..  2020.  AuthentiCAN: a Protocol for Improved Security over CAN. 2020 Fourth World Conference on Smart Trends in Systems, Security and Sustainability (WorldS4). :533–538.
The continuous progress of electronic equipments has influenced car manufacturers, leading to the integration of the latest infotainment technologies and providing connection to external devices, such as mobile phones. Modern cars work with ECUs (Electronic Control Units) that handle user interactions and sensor data, by also sending information to actuators using simple, reliable and efficient networks with fast protocols, like CAN (Controller Area Network). This is the most used vehicular protocol, which allows interconnecting different ECUs, making them interact in a synergic manner. On the down side, there is a security risk related to the exposition of malicious ECU's frames-possibly generated by compromised devices-which can lead to the possibility to remote control all the car equipments (like brakes and others) by an attacker. We propose a solution to this problem, designing an authentication and encryption system above CAN, called AuthentiCAN. Our proposal is tailored for the evolution of CAN called CAN-FD, and avoids the possibility for an attacker to inject malicious frames that are not discarded by the destination ECUs. Also, we avoid the possibility for an attacker to learn the interactions that occur across ECUs, with the objective of maliciously replaying messages-which would lead the actuator's logic to be no longer compliant with the actual data sources. We also present a simulation study of our solution, where we provide an assessment of its overhead, e.g. in terms of reduction of the throughput of data-unit transfer over CAN-FD, caused by the added security features.
2021-01-11
Zhang, H., Zhang, D., Chen, H., Xu, J..  2020.  Improving Efficiency of Pseudonym Revocation in VANET Using Cuckoo Filter. 2020 IEEE 20th International Conference on Communication Technology (ICCT). :763–769.
In VANETs, pseudonyms are often used to replace the identity of vehicles in communication. When vehicles drive out of the network or misbehave, their pseudonym certificates need to be revoked by the certificate authority (CA). The certificate revocation lists (CRLs) are usually used to store the revoked certificates before their expiration. However, using CRLs would incur additional storage, communication and computation overhead. Some existing schemes have proposed to use Bloom Filter to compress the original CRLs, but they are unable to delete the expired certificates and introduce the false positive problem. In this paper, we propose an improved pseudonym certificates revocation scheme, using Cuckoo Filter for compression to reduce the impact of these problems. In order to optimize deletion efficiency, we propose the concept of Certificate Expiration List (CEL) which can be implemented with priority queue. The experimental results show that our scheme can effectively reduce the storage and communication overhead of pseudonym certificates revocation, while retaining moderately low false positive rates. In addition, our scheme can also greatly improve the lookup performance on CRLs, and reduce the revocation operation costs by allowing deletion.
2020-12-28
Padmapriya, S., Valli, R., Jayekumar, M..  2020.  Monitoring Algorithm in Malicious Vehicular Adhoc Networks. 2020 International Conference on System, Computation, Automation and Networking (ICSCAN). :1—6.

Vehicular Adhoc Networks (VANETs) ensures road safety by communicating with a set of smart vehicles. VANET is a subset of Mobile Adhoc Networks (MANETs). VANET enabled vehicles helps in establishing communication services among one another or with the Road Side Unit (RSU). Information transmitted in VANET is distributed in an open access environment and hence security is one of the most critical issues related to VANET. Although each vehicle is not a source of all communications, most contact depends on the information that other vehicles receive from it. That vehicle must be able to assess, determine and respond locally on the information obtained from other vehicles to protect VANET from malicious act. Of this reason, message verification in VANET is more difficult due to the protection and privacy issues of the participating vehicles. To overcome security threats, we propose Monitoring Algorithm that detects malicious nodes based on the pre-selected threshold value. The threshold value is compared with the distrust value which is inherently tagged with each vehicle. The proposed Monitoring Algorithm not only detects malicious vehicles, but also isolates the malicious vehicles from the network. The proposed technique is simulated using Network Simulator2 (NS2) tool. The simulation result illustrated that the proposed Monitoring Algorithm outperforms the existing algorithms in terms of malicious node detection, network delay, packet delivery ratio and throughput, thereby uplifting the overall performance of the network.

Temurnikar, A., Verma, P., Choudhary, J..  2020.  Securing Vehicular Adhoc Network against Malicious Vehicles using Advanced Clustering Technique. 2nd International Conference on Data, Engineering and Applications (IDEA). :1—9.

VANET is one of most emerging and unique topics among the scientist and researcher. Due to its mobility, high dynamic nature and frequently changing topology not predictable, mobility attracts too much to researchers academic and industry person. In this paper, characteristics of VANET ate discussed along with its architecture, proposed work and its ends simulation with results. There are many nodes in VANET and to avoid the load on every node, clustering is applied in VANET. VANET possess the high dynamic network having continuous changing in the topology. For stability of network, a good clustering algorithm is required for enhancing the network productivity. In proposed work, a novel approach has been proposed to make cluster in VANET network and detect malicious node of network for security network.

Makarfi, A. U., Rabie, K. M., Kaiwartya, O., Li, X., Kharel, R..  2020.  Physical Layer Security in Vehicular Networks with Reconfigurable Intelligent Surfaces. 2020 IEEE 91st Vehicular Technology Conference (VTC2020-Spring). :1—6.

This paper studies the physical layer security (PLS) of a vehicular network employing a reconfigurable intelligent surface (RIS). RIS technologies are emerging as an important paradigm for the realisation of smart radio environments, where large numbers of small, low-cost and passive elements, reflect the incident signal with an adjustable phase shift without requiring a dedicated energy source. Inspired by the promising potential of RIS-based transmission, we investigate two vehicular network system models: One with vehicle-to-vehicle communication with the source employing a RIS-based access point, and the other model in the form of a vehicular adhoc network (VANET), with a RIS-based relay deployed on a building. Both models assume the presence of an eavesdropper to investigate the average secrecy capacity of the considered systems. Monte-Carlo simulations are provided throughout to validate the results. The results show that performance of the system in terms of the secrecy capacity is affected by the location of the RIS-relay and the number of RIS cells. The effect of other system parameters such as source power and eavesdropper distances are also studied.

2020-12-14
Boualouache, A., Soua, R., Engel, T..  2020.  SDN-based Misbehavior Detection System for Vehicular Networks. 2020 IEEE 91st Vehicular Technology Conference (VTC2020-Spring). :1–5.
Vehicular networks are vulnerable to a variety of internal attacks. Misbehavior Detection Systems (MDS) are preferred over the cryptography solutions to detect such attacks. However, the existing misbehavior detection systems are static and do not adapt to the context of vehicles. To this end, we exploit the Software-Defined Networking (SDN) paradigm to propose a context-aware MDS. Based on the context, our proposed system can tune security parameters to provide accurate detection with low false positives. Our system is Sybil attack-resistant and compliant with vehicular privacy standards. The simulation results show that, under different contexts, our system provides a high detection ratio and low false positives compared to a static MDS.
Lim, K., Islam, T., Kim, H., Joung, J..  2020.  A Sybil Attack Detection Scheme based on ADAS Sensors for Vehicular Networks. 2020 IEEE 17th Annual Consumer Communications Networking Conference (CCNC). :1–5.
Vehicular Ad Hoc Network (VANET) is a promising technology for autonomous driving as it provides many benefits and user conveniences to improve road safety and driving comfort. Sybil attack is one of the most serious threats in vehicular communications because attackers can generate multiple forged identities to disseminate false messages to disrupt safety-related services or misuse the systems. To address this issue, we propose a Sybil attack detection scheme using ADAS (Advanced Driving Assistant System) sensors installed on modern passenger vehicles, without the assistance of trusted third party authorities or infrastructure. Also, a deep learning based object detection technique is used to accurately identify nearby objects for Sybil attack detection and the multi-step verification process minimizes the false positive of the detection.
Quevedo, C. H. O. O., Quevedo, A. M. B. C., Campos, G. A., Gomes, R. L., Celestino, J., Serhrouchni, A..  2020.  An Intelligent Mechanism for Sybil Attacks Detection in VANETs. ICC 2020 - 2020 IEEE International Conference on Communications (ICC). :1–6.
Vehicular Ad Hoc Networks (VANETs) have a strategic goal to achieve service delivery in roads and smart cities, considering the integration and communication between vehicles, sensors and fixed road-side components (routers, gateways and services). VANETs have singular characteristics such as fast mobile nodes, self-organization, distributed network and frequently changing topology. Despite the recent evolution of VANETs, security, data integrity and users privacy information are major concerns, since attacks prevention is still open issue. One of the most dangerous attacks in VANETs is the Sybil, which forges false identities in the network to disrupt compromise the communication between the network nodes. Sybil attacks affect the service delivery related to road safety, traffic congestion, multimedia entertainment and others. Thus, VANETs claim for security mechanism to prevent Sybil attacks. Within this context, this paper proposes a mechanism, called SyDVELM, to detect Sybil attacks in VANETs based on artificial intelligence techniques. The SyDVELM mechanism uses Extreme Learning Machine (ELM) with occasional features of vehicular nodes, minimizing the identification time, maximizing the detection accuracy and improving the scalability. The results suggest that the suitability of SyDVELM mechanism to mitigate Sybil attacks and to maintain the service delivery in VANETs.
2020-12-07
Allig, C., Leinmüller, T., Mittal, P., Wanielik, G..  2019.  Trustworthiness Estimation of Entities within Collective Perception. 2019 IEEE Vehicular Networking Conference (VNC). :1–8.
The idea behind collective perception is to improve vehicles' awareness about their surroundings. Every vehicle shares information describing its perceived environment by means of V2X communication. Similar to other information shared using V2X communication, collective perception information is potentially safety relevant, which means there is a need to assess the reliability and quality of received information before further processing. Transmitted information may have been forged by attackers or contain inconsistencies e.g. caused by malfunctions. This paper introduces a novel approach for estimating a belief that a pair of entities, e.g. two remote vehicles or the host vehicle and a remote vehicle, within a Vehicular ad hoc Network (VANET) are both trustworthy. The method updates the belief based on the consistency of the data that both entities provide. The evaluation shows that the proposed method is able to identify forged information.
More, P. H., Dongre, M. M..  2019.  Partially Predictable Vehicular Ad-hoc Network: Trustworthiness and Security. 2019 IEEE 5th International Conference for Convergence in Technology (I2CT). :1–5.
VANET is an emerging technology incorporating ad hoc network to accomplish intelligent communications between vehicles, improvement in road traffic efficiency and safety. In some situations movement of vehicles is in a certain range, over particular distance or just in a specific tendency. Such a network can be called as incompletely or partially predictable network. An efficient use of such network, position and motion of nodes as well as relative history in big data is an open issue in vehicular ad hoc network. A hybrid protocol which provides secure and trustworthiness evaluation based routing can be used in VANET. Here Secure Trustworthiness Evaluation Based Routing Protocol is implemented using NS2 software. Its performance is very good in terms of the Average End to End Delay, Packet Delivery Ratio and Normalized Routing Overhead.
2020-11-23
Jolfaei, A., Kant, K., Shafei, H..  2019.  Secure Data Streaming to Untrusted Road Side Units in Intelligent Transportation System. 2019 18th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/13th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE). :793–798.
The paper considers data security issues in vehicle-to-infrastructure communications, where vehicles stream data to a road side unit. We assume aggregated data in road side units can be stored or used for data analytics. In this environment, there are issues in regards to the scalability of key management and computation limitations at the edge of the network. To address these issues, we suggest the formation of groups in the vehicle layer, where a group leader is assigned to communicate with group devices and the road side unit. We propose a lightweight permutation mechanism for preserving the confidentiality of sensory data.
Singh, M., Kim, S..  2018.  Crypto trust point (cTp) for secure data sharing among intelligent vehicles. 2018 International Conference on Electronics, Information, and Communication (ICEIC). :1–4.
Tremendous amount of research is going on in the field of Intelligent vehicles (IVs)in industries and academics. Although, IV supports a better convenience for the society, but it also suffers from some concerns. Security is the major concern in Intelligent vehicle technology, due to its high exposure to data and information communication. The environment of the IV communication has many security vulnerabilities, which cannot be solved by Traditional Security approaches due to their fixed capabilities. Among security, trust, data accuracy and reliability of communication data in the communication channel are the other issues in IV communication. Blockchain is a peer-to-peer, distributed and decentralized technology which is used by the digital currency Bit-coin, to build trust and reliability and it has capability and is feasible to use Blockchain in IV Communication. In this paper, we propose, Blockchain based crypto Trust point (cTp) mechanism for IV communication. Using cTp in the IVs communication environment can provide IV data security and reliability. cTp mechanism accounts for the legitimate and illegitimate vehicles behavior, and rewarding thereby building trust among the vehicles. We also propose a reward based system using cTp (exchange of some cTp among IVs, during successful communication). We use blockchain technology in the Intelligent Transportation System (ITS) for the data management of the cTp. Using ITS, cTp details of every vehicle can be accessed ubiquitously by IVs. We evaluation, our proposal using the intersection use case scenario for intelligent vehicles communication.
2020-11-02
Ma, Y., Bai, X..  2019.  Comparison of Location Privacy Protection Schemes in VANETs. 2019 12th International Symposium on Computational Intelligence and Design (ISCID). 2:79–83.
Vehicular Ad-hoc Networks (VANETs) is a traditional mobile ad hoc network (MANET) used on traffic roads and it is a special mobile ad hoc network. As an intelligent transportation system, VANETs can solve driving safety and provide value-added services. Therefore, the application of VANETs can improve the safety and efficiency of road traffic. Location services are in a crucial position for the development of VANETs. VANETs has the characteristics of open access and wireless communication. Malicious node attacks may lead to the leakage of user privacy in VANETs, thus seriously affecting the use of VANETs. Therefore, the location privacy issue of VANETs cannot be ignored. This paper classifies the attack methods in VANETs, and summarizes and compares the location privacy protection techniques proposed in the existing research.
Xiong, Wenjie, Shan, Chun, Sun, Zhaoliang, Meng, Qinglei.  2018.  Real-time Processing and Storage of Multimedia Data with Content Delivery Network in Vehicle Monitoring System. 2018 6th International Conference on Wireless Networks and Mobile Communications (WINCOM). :1—4.

With the rapid development of the Internet of vehicles, there is a huge amount of multimedia data becoming a hidden trouble in the Internet of Things. Therefore, it is necessary to process and store them in real time as a way of big data curation. In this paper, a method of real-time processing and storage based on CDN in vehicle monitoring system is proposed. The MPEG-DASH standard is used to process the multimedia data by dividing them into MPD files and media segments. A real-time monitoring system of vehicle on the basis of the method introduced is designed and implemented.

Singh, Dhananjay, Tripathi, Gaurav, Shah, Sayed Chhattan, da Rosa Righi, Rodrigo.  2018.  Cyber physical surveillance system for Internet of Vehicles. 2018 IEEE 4th World Forum on Internet of Things (WF-IoT). :546—551.

Internet of Vehicle (IoV) is an essential part of the Intelligent Transportation system (ITS) which is growing exponentially in the automotive industry domain. The term IoV is used in this paper for Internet of Vehicles. IoV is conceptualized for sharing traffic, safety and several other vehicle-related information between vehicles and end user. In recent years, the number of connected vehicles has increased allover the world. Having information sharing and connectivity as its advantage, IoV also faces the challenging task in the cybersecurity-related matters. The future consists of crowded places in an interconnected world through wearable's, sensors, smart phones etc. We are converging towards IoV technology and interactions with crowded space of connected peoples. However, this convergence demands high-security mechanism from the connected crowd as-well-as other connected vehicles to safeguard of proposed IoV system. In this paper, we coin the term of smart people crowd (SPC) and the smart vehicular crowd (SVC) for the Internet of Vehicles (IoV). These specific crowds of SPC and SVC are the potential cyber attackers of the smart IoV. People connected to the internet in the crowded place are known as a smart crowd. They have interfacing devices with sensors and the environment. A smart crowd would also consist of the random number of smart vehicles. With the future converging in to the smart connected framework for crowds, vehicles and connected vehicles, we present a novel cyber-physical surveillance system (CPSS) framework to tackle the security threats in the crowded environment for the smart automotive industry and provide the cyber security mechanism in the crowded places. We also describe an overview of use cases and their security challenges on the Internet of Vehicles.

Anzer, Ayesha, Elhadef, Mourad.  2018.  A Multilayer Perceptron-Based Distributed Intrusion Detection System for Internet of Vehicles. 2018 IEEE 4th International Conference on Collaboration and Internet Computing (CIC). :438—445.

Security of Internet of vehicles (IoV) is critical as it promises to provide with safer and secure driving. IoV relies on VANETs which is based on V2V (Vehicle to Vehicle) communication. The vehicles are integrated with various sensors and embedded systems allowing them to gather data related to the situation on the road. The collected data can be information associated with a car accident, the congested highway ahead, parked car, etc. This information exchanged with other neighboring vehicles on the road to promote safe driving. IoV networks are vulnerable to various security attacks. The V2V communication comprises specific vulnerabilities which can be manipulated by attackers to compromise the whole network. In this paper, we concentrate on intrusion detection in IoV and propose a multilayer perceptron (MLP) neural network to detect intruders or attackers on an IoV network. Results are in the form of prediction, classification reports, and confusion matrix. A thorough simulation study demonstrates the effectiveness of the new MLP-based intrusion detection system.

Sahbi, Roumissa, Ghanemi, Salim, Djouani, Ramissa.  2018.  A Network Model for Internet of vehicles based on SDN and Cloud Computing. 2018 6th International Conference on Wireless Networks and Mobile Communications (WINCOM). :1—4.

Internet of vehicles (IoV) is the evolution of conventional vehicle network (VANET), a recent domain attracting a large number of companies and researchers. It is an integration of three networks: an inter-vehicle network, an intra-vehicle network, and vehicular mobile Internet, in which the vehicle is considered as a smart object equipped with powerful multi-sensors platform, connectivity and communication technologies, enabling it to communicate with the world. The cooperative communication between vehicles and other devices causes diverse challenges in terms of: storage and computing capability, energy of vehicle and network's control and management. Security is very important aspect in IoV and it is required to protect connected cars from cybercrime and accidents. In this article, we propose a network model for IoV based on software Defined Network and Cloud Computing.

2020-10-29
Tomar, Ravi, Awasthi, Yogesh.  2019.  Prevention Techniques Employed in Wireless Ad-Hoc Networks. 2019 International Conference on Advanced Science and Engineering (ICOASE). :192—197.
The paper emphasizes the various aspects of ad-hoc networks. The different types of attacks that affect the system and are prevented by various algorithms mentioned in this paper. Since Ad-hoc wireless networks have no infrastructure and are always unreliable therefore they are subject to many attacks. The black hole attack is seen as one of the dangerous attacks of them. In this attack the malicious node usually absorbs each data packets that are similar to separate holes in everything. Likewise all packets in the network are dropped. For this reason various prevention measures should be employed in the form of routing finding first then the optimization followed by the classification.
Kaur, Jasleen, Singh, Tejpreet, Lakhwani, Kamlesh.  2019.  An Enhanced Approach for Attack Detection in VANETs Using Adaptive Neuro-Fuzzy System. 2019 International Conference on Automation, Computational and Technology Management (ICACTM). :191—197.
Vehicular Ad-hoc Networks (VANETs) are generally acknowledged as an extraordinary sort of Mobile Ad hoc Network (MANET). VANETs have seen enormous development in a decade ago, giving a tremendous scope of employments in both military and in addition non-military personnel exercises. The temporary network in the vehicles can likewise build the driver's capability on the road. In this paper, an effective information dispersal approach is proposed which enhances the vehicle-to-vehicle availability as well as enhances the QoS between the source and the goal. The viability of the proposed approach is shown with regards to the noteworthy gets accomplished in the parameters in particular, end to end delay, packet drop ratio, average download delay and throughput in comparison with the existing approaches.
Kumar, Sushil, Mann, Kulwinder Singh.  2019.  Prevention of DoS Attacks by Detection of Multiple Malicious Nodes in VANETs. 2019 International Conference on Automation, Computational and Technology Management (ICACTM). :89—94.

Vehicular Adhoc Network (VANET), a specialized form of MANET in which safety is the major concern as critical information related to driver's safety and assistance need to be disseminated between the vehicle nodes. The security of the nodes can be increased, if the network availability is increased. The availability of the network is decreased, if there is Denial of Service Attacks (DoS) in the network. In this paper, a packet detection algorithm for the prevention of DoS attacks is proposed. This algorithm will be able to detect the multiple malicious nodes in the network which are sending irrelevant packets to jam the network and that will eventually stop the network to send the safety messages. The proposed algorithm was simulated in NS-2 and the quantitative values of packet delivery ratio, packet loss ratio, network throughput proves that the proposed algorithm enhance the security of the network by detecting the DoS attack well in time.