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Authors: Emmanouil Mastorakis 1 ; Athanasios Salamanis 2 ; Dionysios Kehagias 2 and Dimitrios Tzovaras 2

Affiliations: 1 Aristotle University of Thessaloniki, School of Electrical & Computer Engineering, Thessaloniki and Greece ; 2 Centre for Research & Technology Hellas, Information Technologies Institute, Thessaloniki and Greece

ISBN: 978-989-758-374-2

Keyword(s): Carpooling, Reputation System, Clustering, Robustness, Attacks.

Abstract: Carpooling is a mobility concept that appears to be the answer when it comes to challenges in urban mobility derived by population growth. In carpooling, the same amount of people move with fewer vehicles leading to reduced traffic congestion and consequently to less CO2 emissions, fuel consumption and drivers frustration. However, there has always been scepticism around carpooling due to the inherent mistrust between drivers and passengers. In recent years, some reputation systems have been proposed to reduce the impact of mistrust on carpooling applications. Among them, the work of Salamanis et al. (Salamanis, 2018), in which a reputation assessment mechanism based on clustering users travel preferences, was introduced. In this paper, we provide an extended version of the previous mechanism and we thoroughly evaluate its robustness in relation with different types of malicious attacks and clustering algorithms. In addition, we compare our mechanism with a benchmarking reputation sys tem that utilizes the simple arithmetic mean to calculate reputation values based on users ratings. The evaluation results indicate that the extended reputation assessment mechanism exhibits more robust behavior compared to the benchmarking system in all types of attacks when using the hierarchical clustering algorithm. (More)

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Paper citation in several formats:
Mastorakis, E.; Salamanis, A.; Kehagias, D. and Tzovaras, D. (2019). On the Evaluation of a Cluster-based Reputation Assessment Mechanism for Carpooling Applications.In Proceedings of the 5th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS, ISBN 978-989-758-374-2, pages 232-241. DOI: 10.5220/0007796602320241

@conference{vehits19,
author={Emmanouil Mastorakis. and Athanasios I. Salamanis. and Dionysios D. Kehagias. and Dimitrios Tzovaras.},
title={On the Evaluation of a Cluster-based Reputation Assessment Mechanism for Carpooling Applications},
booktitle={Proceedings of the 5th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS,},
year={2019},
pages={232-241},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007796602320241},
isbn={978-989-758-374-2},
}

TY - CONF

JO - Proceedings of the 5th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS,
TI - On the Evaluation of a Cluster-based Reputation Assessment Mechanism for Carpooling Applications
SN - 978-989-758-374-2
AU - Mastorakis, E.
AU - Salamanis, A.
AU - Kehagias, D.
AU - Tzovaras, D.
PY - 2019
SP - 232
EP - 241
DO - 10.5220/0007796602320241

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