PrivacySignal: Privacy-preserving traffic signal control for intelligent transportation system

Publication Type

Journal Article

Publication Date

2-2022

Abstract

A new trend of using deep reinforcement learning for traffic signal control has become a spotlight in the Intelligent Transportation System (ITS). However, the traditional intelligent traffic signal control system always collects and transmits vehicle information (e.g., vehicle location, speed, etc.) in the form of plaintext, which would result in the leakage of commuters' privacy and thus bring unnecessary troubles to users. In this paper, we propose a privacy-preserving traffic signal control for an intelligent transportation system (PrivacySignal). It relies on the existing road facilities to achieve the privacy of commuters, which guarantees the practicality of the system. Real-time decision-making and confidentiality of the system can be achieved simultaneously via the design of a series of secure and efficient interactive protocols, that are based on additive secret sharing, to perform the deep Q-network (DQN). Moreover, the security of PrivacySignal is testified, meanwhile, the system effectiveness, and the overall efficiency of PrivacySignal is demonstrated through theoretical analysis and simulation experiments. Compared with the existing privacy-preserving schemes of the intelligent traffic signal, PrivacySignal provides a general DQN based privacy-preserving traffic signal control strategy architecture with high efficiency and low-performance loss.

Keywords

Protocols, Real-time systems, Roads, Reinforcement learning, Privacy, Data privacy, Cryptography, Secure multiparty computation, privacy-preserving, deep reinforcement learning, intelligent transportation systems, intelligent traffic signal control

Discipline

Information Security

Research Areas

Cybersecurity

Publication

IEEE Transactions on Intelligent Transportation Systems

Volume

23

Issue

9

First Page

16290

Last Page

16303

ISSN

1524-9050

Identifier

10.1109/TITS.2022.3149600

Publisher

Institute of Electrical and Electronics Engineers

Additional URL

https://doi.org/10.1109/TITS.2022.3149600

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