Dynamic Model Based Malicious Collaborator Detection in Cooperative Tracking

Wang Pi, Pengtao Yang, Dongliang Duan, Chen Chen, Xiang Cheng, Liuqing Yang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The mobility status of vehicles play a crucial role in most tasks of Autonomous Vehicles (AVs) and Intelligent Transportation System (ITS). To operate securely, a precise, stable and robust mobility tracking system is essential. Compared with self-tracking that relies only on mobility observations from on-board sensors (e.g. Global Positioning System (GPS), Inertial Measurement Unit (IMU) and camera), cooperative tracking increases the precision and reliability of mobility data greatly by integrating observations from road side units and nearby vehicles through V2X communications. Nevertheless, cooperative tracking can be quite vulnerable if there are malicious collaborators sending bogus observations in the network. In this paper, we present a dynamic sequential detection algorithm, dynamic model based mean state detection (DMMSD), to exclude bogus mobility data. Simulations validate the effectiveness and robustness of the proposed algorithm as compared with existing approaches.

Original languageEnglish (US)
Title of host publication2020 IEEE Wireless Communications and Networking Conference, WCNC 2020 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728131061
DOIs
StatePublished - May 2020
Externally publishedYes
Event2020 IEEE Wireless Communications and Networking Conference, WCNC 2020 - Seoul, Korea, Republic of
Duration: May 25 2020May 28 2020

Publication series

NameIEEE Wireless Communications and Networking Conference, WCNC
Volume2020-May
ISSN (Print)1525-3511

Conference

Conference2020 IEEE Wireless Communications and Networking Conference, WCNC 2020
CountryKorea, Republic of
CitySeoul
Period5/25/205/28/20

Bibliographical note

Funding Information:
This work was in part supported by the Ministry National Key Research and Development Project under Grant 2017YFE0121400, Guandong Key R&D Project under Grant 2019B010153003, the open research fund of Key Laboratory of Wireless Sensor Network & Communication under Grant 2017003, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, and the National Science Foundation under Grants CNS-1932413 and CNS-1932139.

Fingerprint Dive into the research topics of 'Dynamic Model Based Malicious Collaborator Detection in Cooperative Tracking'. Together they form a unique fingerprint.

Cite this