75 research outputs found

    Detection of Sybil attack in vehicular ad hoc networks by analyzing network performance

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    Vehicular ad hoc network (VANET) is an emerging technology which can be very helpful for providing safety and security as well as for intelligent transportation services. But due to wireless communication of vehicles and high mobility it has certain security issues which cost the safety and security of people on the road. One of the major security concerns is the Sybil attack in which the attacker creates dummy identities to gain high influence in the network that causes delay in some services and fake voting in the network to misguide others. The early detection of this attack can prevent people from being misguided by the attacker and save them from getting into any kind of trap. In this research paper, Sybil attack is detected by first applying the Poisson distribution algorithm to predict the traffic on the road and in the second approach, analysis of the network performance for packet delivery ratio (PDR) is performed in malign and benign environment. The simulation result shows that PDR decreases in presence of fake vehicles in the network. Our approach is simple and effective as it does not require high computational overhead and also does not violate the privacy issues of people in the network

    MARINE: Man-in-the-middle attack resistant trust model IN connEcted vehicles

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    Vehicular Ad-hoc NETwork (VANET), a novel technology holds a paramount importance within the transportation domain due to its abilities to increase traffic efficiency and safety. Connected vehicles propagate sensitive information which must be shared with the neighbors in a secure environment. However, VANET may also include dishonest nodes such as Man-in-the-Middle (MiTM) attackers aiming to distribute and share malicious content with the vehicles, thus polluting the network with compromised information. In this regard, establishing trust among connected vehicles can increase security as every participating vehicle will generate and propagate authentic, accurate and trusted content within the network. In this paper, we propose a novel trust model, namely, Man-in-the-middle Attack Resistance trust model IN connEcted vehicles (MARINE), which identifies dishonest nodes performing MiTM attacks in an efficient way as well as revokes their credentials. Every node running MARINE system first establishes trust for the sender by performing multi-dimensional plausibility checks. Once the receiver verifies the trustworthiness of the sender, the received data is then evaluated both directly and indirectly. Extensive simulations are carried out to evaluate the performance and accuracy of MARINE rigorously across three MiTM attacker models and the bench-marked trust model. Simulation results show that for a network containing 35% MiTM attackers, MARINE outperforms the state of the art trust model by 15%, 18%, and 17% improvements in precision, recall and F-score, respectively.N/A

    Analysis of cyber risk and associated concentration of research (ACR)² in the security of vehicular edge clouds

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    Intelligent Transportation Systems (ITS) is a rapidly growing research space with many issues and challenges. One of the major concerns is to successfully integrate connected technologies, such as cloud infrastructure and edge cloud, into ITS. Security has been identified as one of the greatest challenges for the ITS, and security measures require consideration from design to implementation. This work focuses on providing an analysis of cyber risk and associated concentration of research (ACR2). The introduction of ACR2 approach can be used to consider research challenges in VEC and open up further investigation into those threats that are important but under-researched. That is, the approach can identify very high or high risk areas that have a low research concentration. In this way, this research can lay the foundations for the development of further work in securing the future of ITS

    A hierarchical detection method in external communication for self-driving vehicles based on TDMA

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    Security is considered a major challenge for self-driving and semi self-driving vehicles. These vehicles depend heavily on communications to predict and sense their external environment used in their motion. They use a type of ad hoc network termed Vehicular ad hoc networks (VANETs). Unfortunately, VANETs are potentially exposed to many attacks on network and application level. This paper, proposes a new intrusion detection system to protect the communication system of self-driving cars; utilising a combination of hierarchical models based on clusters and log parameters. This security system is designed to detect Sybil and Wormhole attacks in highway usage scenarios. It is based on clusters, utilising Time Division Multiple Access (TDMA) to overcome some of the obstacles of VANETs such as high density, high mobility and bandwidth limitations in exchanging messages. This makes the security system more efficient, accurate and capable of real time detection and quick in identification of malicious behaviour in VANETs. In this scheme, each vehicle log calculates and stores different parameter values after receiving the cooperative awareness messages from nearby vehicles. The vehicles exchange their log data and determine the difference between the parameters, which is utilised to detect Sybil attacks and Wormhole attacks. In order to realize efficient and effective intrusion detection system, we use the well-known network simulator (ns-2) to verify the performance of the security system. Simulation results indicate that the security system can achieve high detection rates and effectively detect anomalies with low rate of false alarms

    A multi-tier trust-based security mechanism for vehicular ad-hoc network communications

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    Securing communications in vehicle ad hoc networks is crucial for operations. Messages exchanged in vehicle ad hoc network communications hold critical information such as road safety information, or road accident information and it is essential these packets reach their intended destination without any modification. A significant concern for vehicle ad hoc network communications is that malicious vehicles can intercept or modify messages before reaching their intended destination. This can hamper vehicle ad hoc network operations and create safety concerns. The multi-tier trust management system proposed in this paper addresses the concern of malicious vehicles in the vehicle ad hoc network using three security tiers. The first tier of the proposed system assigns vehicles in the vehicle ad hoc network a trust value based on behaviour such as processing delay, packet loss and prior vehicle behavioural history. This will be done by selecting vehicles as watchdogs to observe the behaviour of neighbouring vehicles and evaluate the trust value. The second tier is to protect the watchdogs, which is done by watchdogs’ behaviour history. The third security tier is to protect the integrity of data used for trust value calculation. Results show that the proposed system is successful in identifying malicious vehicles in the VANET. It also improves the packet delivery ratio and end-to-end delay of the vehicle ad hoc network in the presence of malicious vehicles
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