Biblio
Trust estimation of vehicles is vital for the correct functioning of Vehicular Ad Hoc Networks (VANETs) as it enhances their security by identifying reliable vehicles. However, accurate trust estimation still remains distant as existing works do not consider all malicious features of vehicles, such as dropping or delaying packets, altering content, and injecting false information. Moreover, data consistency of messages is not guaranteed here as they pass through multiple paths and can easily be altered by malicious relay vehicles. This leads to difficulty in measuring the effect of content tampering in trust calculation. Further, unreliable wireless communication of VANETs and unpredictable vehicle behavior may introduce uncertainty in the trust estimation and hence its accuracy. In this view, we put forward three trust factors - captured by fuzzy sets to adequately model malicious properties of a vehicle and apply a fuzzy logic-based algorithm to estimate its trust. We also introduce a parameter to evaluate the impact of content modification in trust calculation. Experimental results reveal that the proposed scheme detects malicious vehicles with high precision and recall and makes decisions with higher accuracy compared to the state-of-the-art.
Recently, several cross-layer protocols have been designed for vehicular networks to optimize data dissemination by ensuring internal communications between routing and MAC layers. In this context, a cross-layer protocol, called TDMA-aware Routing Protocol for Multi-hop communications (TRPM), was proposed in order to efficiently select a relay node based on time slot scheduling information obtained from the MAC layer. However, due to the constant evolution of cyber-attacks on the routing and MAC layers, data dissemination in vehicular networks is vulnerable to several types of attack. In this paper, we identify the different attack models that can disrupt the cross-layer operation of the TRPM protocol and assess their impact on performance through simulation. Several new vulnerabilities related to the MAC slot scheduling process are identified. Exploiting of these vulnerabilities would lead to severe channel capacity wastage where up to half of the free slots could not be reserved.
Nowadays, Vehicular Ad hoc Networks (VANETs) are popularly known as they can reduce traffic and road accidents. These networks need several security requirements, such as anonymity, data authentication, confidentiality, traceability and cancellation of offending users, unlinkability, integrity, undeniability and access control. Authentication of the data and sender are most important security requirements in these networks. So many authentication schemes have been proposed up to now. One of the well-known techniques to provide users authentication in these networks is the authentication based on the smartcard (ASC). In this paper, we propose an ASC scheme that not only provides necessary security requirements such as anonymity, traceability and unlinkability in the VANETs but also is more efficient than the other schemes in the literatures.
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.
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.