Abstract
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.
Highlights
Autonomous vehicles are poised to change the future of transportation
Autonomous vehicles possess significantly more computational power than a microcontroller, most of their resources are dedicated to performing on-board functionality, such as object recognition and communication broadcasting, within vehicle-to-vehicle (V2V) transactions; the problem of computational and storage limitations is relevant to autonomous vehicles (AVs), too [51]
With an average operating error of 0.175 and reporting error of 0.160, the data indicates that the simulation was able to effectively distinguish malicious vehicles from normal ones
Summary
Autonomous vehicles are poised to change the future of transportation They have the capability of increasing mobility for non-drivers and mobility independence for the less affluent [1]. They should result in reduced traffic, enhanced safety, reduced energy consumption, and lower pollution [1]. A vehicle’s reputation may be used to inform other vehicles’ decisions about which details and transactions to accept It has potentially broader uses, such as for rating purposes by insurance companies, where premium prices might be decreased for vehicles that demonstrate stable performance. The system is proposed and assessed, via simulation, to characterize its efficacy at performing its primary function: accurately identifying malicious vehicles under various environmental conditions The paper concludes with a discussion of the work presented and key topics for future study
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