Intelligent Agents in Mobile Vehicular Ad-Hoc Networks: Leveraging Trust Modeling Based on Direct Experience with Incentives for Honesty

Minhas, Umar Farooq; Zhang, Jie; Tran, Thomas; Cohen, Robin

doi:10.1109/wi-iat.2010.66

Cited by 35 publications

(28 citation statements)

References 3 publications

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“…Literature [10,11] proposes a multi-tiered trust modeling framework that includes role-based trust, experience-based trust, and majority-based trust, and can limit the number of reports received. In [12], a trust-based VANETs privacy protection model was proposed.…”

Section: Trust-based Vcps Security Methods Analysismentioning

confidence: 99%

Research on Communication Security of VCPS

Xiao¹,

Zhang²

2018

Proceedings of the 2018 International Conference on Network, Communication, Computer Engineering (NCCE 2018)

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Abstract. VCPS (Vehicular Cyber Physical System) effectively improves road safety and improves driver's driving environment. However, due to the large scale of the VANET network, the predictability of the trajectory, and the open nature of the wireless channel, it is more vulnerable to privacy and security threats. This paper proposes security requirements for VCPS communication, security threats and trust-based security analysis.

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Section: Trust-based Vcps Security Methods Analysismentioning

confidence: 99%

Research on Communication Security of VCPS

Xiao¹,

Zhang²

2018

Proceedings of the 2018 International Conference on Network, Communication, Computer Engineering (NCCE 2018)

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“…In this paper, we assume communication through vanet technologies, aiming to be consistent with the IEEE802.11p standard. A trust model in [14] employs a penalty in case of misleading reports. Experiments with altruist/selfish agents in vanets [13] shown that average speed increased when the vehicular agents cooperate.…”

Section: B Multi-agent Vehicular Simulationmentioning

confidence: 99%

Assisting drivers during overtaking using Car-2-Car communication and multi-agent systems

Cara

Groza

Zaporojan

et al. 2016

2016 IEEE 12th International Conference on Intelligent Computer Communication and Processing (ICCP)

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“…In this section, we outline our original framework for modeling trust in VANET environments ( [1][2][3]). We consider the driver of each vehicle in our VANET environment to be represented by an agent.…”

Section: Background: Multi-faceted Trust Modelmentioning

confidence: 99%

“…The critical distinction of direct or indirect reporting then influences the values set for α and β, introducing greater penalties for disappointment with direct advice. In [2] we discuss at greater length the incentives to honesty that are introduced within this framework; for brevity, we omit that discussion in this paper.…”

Section: T a (B) ← T A (B) + β(1 ? T A (B))mentioning

confidence: 99%

A trust-based framework for vehicular travel with non-binary reports and its validation via an extensive simulation testbed

et al. 2014

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In this paper, we offer an algorithm for intelligent decision making about travel path planning in mobile vehicular ad-hoc networks (VANETs), for scenarios where agents representing vehicles exchange reports about traffic. One challenge that arises is how best to model the trustworthiness of those traffic reports. To this end, we outline an algorithm for effectively soliciting, receiving and analyzing the trustworthiness of these reports, to drive a vehicle?s decision about the path to follow. Distinct from earlier work, we clarify the need for specifying the conditions under which reports are exchanged and for processing non-binary reports, culminating in a proposed algorithm to achieve that processing, as part of the trust modeling and path planning. To validate our approach we then offer a detailed evaluation framework that achieves large scale simulation of traffic, travel and reporting of information, confirming the value of our proposed approach by demonstrating the average speed of vehicles which follow our algorithm (compared to ones that do not). This experimental framework is promoted as a significant contribution towards the goal of evaluating trust algorithms for intelligent decision making in traffic scenarios.

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Intelligent Agents in Mobile Vehicular Ad-Hoc Networks: Leveraging Trust Modeling Based on Direct Experience with Incentives for Honesty

Cited by 35 publications

References 3 publications

Research on Communication Security of VCPS

Research on Communication Security of VCPS

Assisting drivers during overtaking using Car-2-Car communication and multi-agent systems

A trust-based framework for vehicular travel with non-binary reports and its validation via an extensive simulation testbed

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