Detection of incorrect position information using speed and time span verification in VANET

Grover, Jyoti; Gaur, Manoj Singh; Laxmi, Vijay; Tiwari, Rakesh

doi:10.1145/2388576.2388583

Cited by 16 publications

(8 citation statements)

References 12 publications

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“…Consider an example traffic scenario where the vehicles travel at a rate of 80 km/h, and the transmission range of RSU is 500 m. Then, the maximum time for which a vehicle stays in the range of an RSU is 22.50 s. 34 To determine the actual computation time required by our approach in such a scenario, we performed a series of simulation experiments with realistic traffic data. From the results of the simulation shown in Figure 9, it is evident that our approach can detect the Sybil attacker within a minimum observation time of 2 s at a 500-m transmission range.…”

Section: Computation Time Required In a Realistic Vehicular Trafficmentioning

confidence: 99%

A collaborative strategy for detection and eviction of Sybil attacker and Sybil nodes in VANET

Krishnan

Kumar

2020

Int J Communication

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Summary Vehicular ad hoc network (VANET) is a part of the intelligent transportation system (ITS) that provides safety and nonsafety applications. The high mobility of vehicles and the wireless communication environment in VANET makes it vulnerable to various attacks. One among them is the Sybil attack, where a Sybil attacker creates multiple fake identities called Sybil nodes that disrupt the functionality of VANET. Most of the existing solutions in the literature discuss identifying the Sybil nodes (virtual); very few works exist to determine the Sybil attacker (source node that generates Sybil nodes). In this paper, we propose a computation less heuristic approach that focuses on detecting the Sybil attacker and its Sybil nodes using signal strength measurements and Euclidean distance as the detection parameters. The central VANET server, Road Side Units (RSUs), and vehicles collaborate in the detection process, which improves the accuracy of our approach. The core of the approach is a reward‐based system, where the vehicle rewards are determined by collecting RSUs' feedback about the vehicle behavior. From simulation experiments, it is evident that our proposed approach achieves a maximum detection rate of 99.89% and a false positive rate of 0.012% than the existing techniques.

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Section: Computation Time Required In a Realistic Vehicular Trafficmentioning

confidence: 99%

A collaborative strategy for detection and eviction of Sybil attacker and Sybil nodes in VANET

Krishnan

Kumar

2020

Int J Communication

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“…In VANETs, vehicle are equipped with an OBU. The RSU is deployed on roadside to monitor network nodes' behaviour information [15] and provide Internet facility access to pasenger on wheels. The CAs distribute security-related information through RSU like public key, private key and privacy-related information in VANETs (Fig.…”

Section: Vehicular Ad Hoc Networkmentioning

confidence: 99%

“…This detection scheme minimizes overhead on other mobile vehicles in the network. For safety alerts, position verification is important, and vehicle will wait for RSU response which creates more latency [15].…”

Section: Fig 3 Malicious Information Detection Schemes In Vanetsmentioning

confidence: 99%

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A survey of local/cooperative-based malicious information detection techniques in VANETs

Arshad

Ullah

Ahmad

et al. 2018

J Wireless Com Network

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Vehicular ad hoc networks (VANETs) are emerged technology where vehicles and roadside units (RSUs) communicate with each other. VANETs can be categorized as a subbranch of mobile ad hoc networks (MANETs). VANETs help to improve traffic efficiency and safety and provide infotainment facility as well. The dissemination of messages must be relayed through nodes in VANETs. However, it is possible that a node may propagate false information in a network due to its malicious behaviour or selfishness. False information in VANETs can change drivers' behaviour and create disastrous consequences in the network. Therefore, sometimes false safety messages may endanger human life. To avoid any lass, it is more important to detect and avoid false messages. This paper has explained some important algorithms that can detect false messages in VANETs. The categorization of false message detection schemes based on local and cooperative behaviour has been presented in this article. The limitations and consequences of existing schemes as well as future work has been discussed. Keywords: VANETs, MANETs, Misbehaviour, False message detection, Security ReviewThis article analyses Single/local and Cooperative based malicious information detection techniques in VANETs. Single/local based detection schemes are further comprised of plausibility, consistency and single node behavior. However, these techniques performances are not upto the mark, because of single node reliance. The cooperative based detection techniques are more efficient than Single/local based detection schemes. The prerequisites for these scheme need more nodes, unlike Single/local based detection schemes. These techniques are classified based on consistency and behavior with neighbors. Trust-based detection techniques are analysed on previous communication history. However, these scheme needs a honest and sufficient number of nodes for reliable result.

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“…The nodes in the network may act as routers and play a key role in establishing and maintaining routes between communicating nodes. Vehicles in VANET can communicate with each other directly forming what is known as Vehicle to Vehicle (V2V) communication (Al-Sultan et al, 2014), or can communicate with Road Side Units (RSUs) forming Vehicle to Infrastructure (V2I) communication (Grover et al, 2012). The communication is established between vehicles based on the Dedicated Short Range Communication (DSRC) which utilizes the IEEE 802.11p (Gerla and Kleinrock, 2011).…”

Section: Introductionmentioning

confidence: 99%

Routing and the Impact of Group Mobility Model in VANETs

Al‐Qassas¹

2016

Journal of Computer Science

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Group vehicular applications could play a vital role in our life, whether these applications are safety-oriented or convenience-oriented applications. The group concept has also been used in support of many solutions in VANETs. Reference Point Group Mobility model (RPGM) is a popular group mobility model and has been used heavily in the literature. In order to study the impact of this mobility model on routing in VANETs, two well-known protocols are considered, namely AODV and AOMDV, as representatives of single-path and multipath routing, respectively. These protocols have shown performance merits over other routing protocols and they have a vital role in other wireless networks including MANETs and Wireless Mesh Networks. This paper provides a thorough evaluation of these protocols, by examining them under various potential realistic scenarios, under the RPGM mobility model. To the best of knowledge, this is the first study that examines the behaviour of the two protocols under the RPGM mobility model. The results from extensive simulations have shown that both protocols have comparable performance merits when the number of communicating nodes is low. However, increasing the number of communicating nodes has demonstrated a performance advantage for AOMDV, in the majority of the performance metrics used in the paper.

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Detection of incorrect position information using speed and time span verification in VANET

Cited by 16 publications

References 12 publications

A collaborative strategy for detection and eviction of Sybil attacker and Sybil nodes in VANET

A collaborative strategy for detection and eviction of Sybil attacker and Sybil nodes in VANET

A survey of local/cooperative-based malicious information detection techniques in VANETs

Routing and the Impact of Group Mobility Model in VANETs

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