NB-FTBM Model for Entity Trust Evaluation in Vehicular Ad Hoc Network Security

Sumithra, S.; Vadivel, R.

doi:10.1007/978-3-030-20615-4_13

Cited by 3 publications

(3 citation statements)

References 17 publications

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“…The fundamental purpose of all simulations is to enhance saved rebroadcast, low bandwidth, and raise the saved broadcast ratio, that leads to significant storm mitigation and, ultimately, fewer packet conflicts in the connection [32]. Then, using a random evaluation delay versus computed waiting time, simulation compares the counter-based and probability-based systems (using the mean of multiple thresholds).Simulation examines at how the density, speed, and mobility of the nodes affect the protocols' performance [33].…”

Section: Resultsmentioning

confidence: 99%

Analyzing the Effectiveness of TCA-CBB by Comparing Various VANET Broadcasting Algorithms in Terms of Quality of Service

Sumithra

Vadivel

2021

Wireless Pers Commun

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Broadcasting on Vehicular Ad Hoc Networks (VANET) is quickly becoming a hot topic. One of the complications presented by this topic is that it is limited to Vehicle-to-Vehicle (V2V) situations rather than employing communications networks (such as broadband connections). Intelligent Transportation Systems (ITS) are primarily focused on the distribution of emergency messages as well as basic information. The IEEE has recognized Wireless Access in Vehicular Environment (WAVE) as the standard for this message distribution. IEEE 802.11p and Dedicated Short Range Communication (DSRC) are two Medium Access Control (MAC) layer protocols supported by this WAVE. At high vehicle density scenarios, the increasing rate of broadcasting will slow down the performance of the broadcasting method and increase the packet loss ratio. In this paper, various broadcasting algorithms are compared in terms of Quality of Service (QoS) to analyze the best algorithm which achieves high packet delivery ratio and improve the performance at high vehicle density scenario. A new broadcasting algorithm Traffic Condition Aware Customized Beacon Broadcasting (TCA-CBB) method is introduced and compared with other methods. At the end of the performance evaluation between the broadcasting methods, it is proved that the proposed TCA-CBB algorithms shows best results.

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Section: Resultsmentioning

confidence: 99%

Analyzing the Effectiveness of TCA-CBB by Comparing Various VANET Broadcasting Algorithms in Terms of Quality of Service

Sumithra

Vadivel

2021

Wireless Pers Commun

Self Cite

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“…Given the class label of the tuple. The probability is estimated as follows (6) We can easily estimate the probabilities of the factors representing Equation 6. In Equation 6 factor (x i ) refers to the values of the attributes.…”

Section: New Modified Naïve Bayesian Classification Methods To Selementioning

confidence: 99%

“…Sumitra and Vadivel [6], have proposed an entity oriented trust model namely NB-FTBM (Naïve Bayesian Fuzzy Trust Boundary Model), Their model uses two modules namely Entity Identification (E-ID) and Entity Reputation (E-RP), used to identify the vehicular entities and to compute the reputation scores of the entities. Authors also suggested a unique fuzzy based decision making technique, used by the entities to take appropriate decision for the information received.…”

Section: Related Studymentioning

confidence: 99%

DyReT: A Dynamic Rule Framing Engine Equipped With Trust Management for Vehicular Networks

et al. 2020

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Managing a dynamic traffic system is a challenging task in vehicular environments. Clarity of vehicular data for efficient decision making is vital in Intelligent Transportation Systems (ITS). Huge volumes of vehicular data are collected and processed during vehicular transactions. Pre-processing the huge amounts of raw vehicular data followed by framing effective traffic rules to take appropriate rapid decisions by the ITS on the vehicles continues to be a challenging problem. Most of the current studies done on ITS have proposed decision making strategies to handle only specific vehicular events and many lacked framing intelligent dynamic decision rules along with appropriate actions, representing all traffic events prevailing in the vehicular environment. This study proposes a versatile decision engine implanted with a two-stage mechanism. In the first stage, we propose a novel data cleaning algorithm to identify and remove dirty data from the voluminous vehicular dataset. In the second stage, a unique rule framing mechanism is suggested to frame dynamic traffic rules along with their actions using real-time vehicular data. The vehicular entities take suitable decisions to respond to the traffic events based on these rules and their associated actions. A new Naïve Bayesian classifier is proposed in this study to test the new rule framed with the trained rules set, either to accept or reject the new rule for further processing. The algorithms are developed and implemented using machine learning concepts. Experimental and comparative analysis was carried out with other related referred studies to evaluate the performance of the proposed algorithms. Although the proposed decision engine is generic enough for decision making in most ITS use-cases, discussion in this article elaborates on its applicability in use-cases provisioning trust management. INDEX TERMS Vehicular networks, artificial intelligence, data pre-processing, rule framing, trust management.

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On trust management in vehicular ad hoc networks: A comprehensive review

Che¹,

Duan²,

Li³

et al. 2022

Front. Internet Things

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Security issues have always posed a major threat and challenge to the Internet of Things (IoTs), especially the vehicular ad-hoc networks (VANETs), a subcategory of IoTs in the automotive field. The traditional methods to solve these ever-growing security issues in VANETs are mainly cryptography-based. As an effective and efficient complement to those solutions, trust management solutions and reputation models have been widely explored to deal with malicious or selfish vehicle intrusion and forged data spoofing, with the aim of enhancing the overall security, reliability, trustworthiness, and impartiality of VANETs. For the integrity of the article, this survey begins with providing the background information of VANETs, including the basic components and general architecture. Then, many attacks in VANETs are investigated, analyzed, and compared to understand the functional relevance of the following trust and reputation methods. Various approaches offer various countermeasures against these types of attacks. At the same time, the latest development of emerging technologies such as blockchain, software-defined network, and cloud computing opens up new possibilities for more and more promising trust and reputation management models and systems in VANETs. After that, the survey reviews the most important trust and reputation models and schemes which are widely mentioned in the literature based on our developed technique-based taxonomy, in contrast to the popular “entity-centric, data-centric, hybrid” taxonomy in the field, to adapt to the recent technological development of these management schemes in VANETs. Finally, discussions and speculations on the future direction of research into the trust and reputation management in VANETs are presented.

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NB-FTBM Model for Entity Trust Evaluation in Vehicular Ad Hoc Network Security

Cited by 3 publications

References 17 publications

Analyzing the Effectiveness of TCA-CBB by Comparing Various VANET Broadcasting Algorithms in Terms of Quality of Service

Analyzing the Effectiveness of TCA-CBB by Comparing Various VANET Broadcasting Algorithms in Terms of Quality of Service

DyReT: A Dynamic Rule Framing Engine Equipped With Trust Management for Vehicular Networks

On trust management in vehicular ad hoc networks: A comprehensive review

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