Secure intelligent traffic light control using fog computing
As the number of vehicles grows, traffic efficiency is becoming a worldwide problem. Intelligent transportation system aims to improve the traffic efficiency, where intelligent traffic light control is an important component. Existing intelligent traffic light control systems face some challenges, e...
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Published in | Future generation computer systems Vol. 78; pp. 817 - 824 |
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Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
Published |
Elsevier B.V
01.01.2018
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Subjects | |
Online Access | Get full text |
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Abstract | As the number of vehicles grows, traffic efficiency is becoming a worldwide problem. Intelligent transportation system aims to improve the traffic efficiency, where intelligent traffic light control is an important component. Existing intelligent traffic light control systems face some challenges, e.g., avoiding heavy roadside sensors, resisting malicious vehicles and avoiding single-point failure. To cope with those challenges, we propose two secure intelligent traffic light control schemes using fog computing whose security are based on the hardness of the computational Diffie–Hellman puzzle and the hash collision puzzle respectively. The two schemes assume the traffic lights are fog devices. The first scheme is a simple extension of a recent scheme for defending denial-of-service attacks. We show this simple extension is not efficient when the vehicle density is high. The second scheme is much more efficient and is fog device friendly. Even the vehicle density is high, the traffic light may verify the validity of the vehicles efficiently.
•Our schemes may resist the attacks from malicious vehicles.•Our schemes can avoid the problem of single-point failure.•Our improved scheme is fog device friendly. |
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AbstractList | As the number of vehicles grows, traffic efficiency is becoming a worldwide problem. Intelligent transportation system aims to improve the traffic efficiency, where intelligent traffic light control is an important component. Existing intelligent traffic light control systems face some challenges, e.g., avoiding heavy roadside sensors, resisting malicious vehicles and avoiding single-point failure. To cope with those challenges, we propose two secure intelligent traffic light control schemes using fog computing whose security are based on the hardness of the computational Diffie–Hellman puzzle and the hash collision puzzle respectively. The two schemes assume the traffic lights are fog devices. The first scheme is a simple extension of a recent scheme for defending denial-of-service attacks. We show this simple extension is not efficient when the vehicle density is high. The second scheme is much more efficient and is fog device friendly. Even the vehicle density is high, the traffic light may verify the validity of the vehicles efficiently.
•Our schemes may resist the attacks from malicious vehicles.•Our schemes can avoid the problem of single-point failure.•Our improved scheme is fog device friendly. |
Author | Shen, Jian Dai, Feifei Liu, Jian Zhang, Yuanfei Li, Jiangtao Zhang, Lei Meng, Xinyu |
Author_xml | – sequence: 1 givenname: Jian orcidid: 0000-0002-0482-8951 surname: Liu fullname: Liu, Jian organization: Shanghai Key Laboratory of Trustworthy Computing, School of Computer Science and Software Engineering, East China Normal University, China – sequence: 2 givenname: Jiangtao surname: Li fullname: Li, Jiangtao organization: Shanghai Key Laboratory of Trustworthy Computing, School of Computer Science and Software Engineering, East China Normal University, China – sequence: 3 givenname: Lei surname: Zhang fullname: Zhang, Lei email: leizhang@sei.ecnu.edu.cn organization: Shanghai Key Laboratory of Trustworthy Computing, School of Computer Science and Software Engineering, East China Normal University, China – sequence: 4 givenname: Feifei surname: Dai fullname: Dai, Feifei organization: Shanghai Key Laboratory of Trustworthy Computing, School of Computer Science and Software Engineering, East China Normal University, China – sequence: 5 givenname: Yuanfei surname: Zhang fullname: Zhang, Yuanfei organization: Shanghai Key Laboratory of Trustworthy Computing, School of Computer Science and Software Engineering, East China Normal University, China – sequence: 6 givenname: Xinyu surname: Meng fullname: Meng, Xinyu organization: Shanghai Key Laboratory of Trustworthy Computing, School of Computer Science and Software Engineering, East China Normal University, China – sequence: 7 givenname: Jian surname: Shen fullname: Shen, Jian organization: School of Computer and Software, Nanjing University of Information Science and Technology, China |
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SubjectTerms | Intelligent transportation system Puzzle Traffic light control VANET |
Title | Secure intelligent traffic light control using fog computing |
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