Evaluation of a Reputation Management Technique for Autonomous Vehicles
Future autonomous vehicles will rely heavily on sharing and communicating information with other vehicles to maximize their efficiency. These interactions, which will likely include details about the positions of surrounding vehicles and obstacles on the road, are essential to their decision-making...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-01-01
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| Series: | Future Internet |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1999-5903/14/2/31 |
| _version_ | 1797480055901782016 |
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| author | Darius Kianersi Suraj Uppalapati Anirudh Bansal Jeremy Straub |
| author_facet | Darius Kianersi Suraj Uppalapati Anirudh Bansal Jeremy Straub |
| author_sort | Darius Kianersi |
| collection | DOAJ |
| description | Future autonomous vehicles will rely heavily on sharing and communicating information with other vehicles to maximize their efficiency. These interactions, which will likely include details about the positions of surrounding vehicles and obstacles on the road, are essential to their decision-making and the prevention of accidents. However, malicious vehicles—those that intentionally communicate false information—have the capacity to adversely influence other vehicles in the network. This paper presents and evaluates a reputation management system, capable of identifying malicious actors, to mitigate their effects on the vehicle network. The viability of multiple report weighting schemes to calculate reputation is evaluated through a simulation, and a blockchain-based backend for the reputation management system to securely maintain and communicate reputation data is proposed. Storage and computational challenges are considered. This paper shows that weighting schemas, related to the number and reputation of witnesses, positively affect the accuracy of the model and are able to identify malicious vehicles in a network with consistent accuracy and scalability. |
| first_indexed | 2024-03-09T21:54:40Z |
| format | Article |
| id | doaj.art-42d3f61b92ee4fd099f3bc97b03cafa8 |
| institution | Directory Open Access Journal |
| issn | 1999-5903 |
| language | English |
| last_indexed | 2024-03-09T21:54:40Z |
| publishDate | 2022-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Future Internet |
| spelling | doaj.art-42d3f61b92ee4fd099f3bc97b03cafa82023-11-23T19:59:36ZengMDPI AGFuture Internet1999-59032022-01-011423110.3390/fi14020031Evaluation of a Reputation Management Technique for Autonomous VehiclesDarius Kianersi0Suraj Uppalapati1Anirudh Bansal2Jeremy Straub3Thomas Jefferson School, 6560 Braddock Rd., Alexandria, VA 22312, USAThomas Jefferson School, 6560 Braddock Rd., Alexandria, VA 22312, USAThomas Jefferson School, 6560 Braddock Rd., Alexandria, VA 22312, USADepartment of Computer Science, North Dakota State University, Fargo, ND 58102, USAFuture autonomous vehicles will rely heavily on sharing and communicating information with other vehicles to maximize their efficiency. These interactions, which will likely include details about the positions of surrounding vehicles and obstacles on the road, are essential to their decision-making and the prevention of accidents. However, malicious vehicles—those that intentionally communicate false information—have the capacity to adversely influence other vehicles in the network. This paper presents and evaluates a reputation management system, capable of identifying malicious actors, to mitigate their effects on the vehicle network. The viability of multiple report weighting schemes to calculate reputation is evaluated through a simulation, and a blockchain-based backend for the reputation management system to securely maintain and communicate reputation data is proposed. Storage and computational challenges are considered. This paper shows that weighting schemas, related to the number and reputation of witnesses, positively affect the accuracy of the model and are able to identify malicious vehicles in a network with consistent accuracy and scalability.https://www.mdpi.com/1999-5903/14/2/31autonomous vehiclesreputationtrustcybersecuritytransportationblockchain |
| spellingShingle | Darius Kianersi Suraj Uppalapati Anirudh Bansal Jeremy Straub Evaluation of a Reputation Management Technique for Autonomous Vehicles Future Internet autonomous vehicles reputation trust cybersecurity transportation blockchain |
| title | Evaluation of a Reputation Management Technique for Autonomous Vehicles |
| title_full | Evaluation of a Reputation Management Technique for Autonomous Vehicles |
| title_fullStr | Evaluation of a Reputation Management Technique for Autonomous Vehicles |
| title_full_unstemmed | Evaluation of a Reputation Management Technique for Autonomous Vehicles |
| title_short | Evaluation of a Reputation Management Technique for Autonomous Vehicles |
| title_sort | evaluation of a reputation management technique for autonomous vehicles |
| topic | autonomous vehicles reputation trust cybersecurity transportation blockchain |
| url | https://www.mdpi.com/1999-5903/14/2/31 |
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