Secure Distributed Adaptive Platooning Control of Automated Vehicles Over Vehicular Ad-Hoc Networks Under Denial-of-Service Attacks

This article deals with the problem of secure distributed adaptive platooning control of automated vehicles over vehicular ad-hoc networks (VANETs) in the presence of intermittent denial-of-service (DoS) attacks. The platoon, which is wirelessly connected via directed vehicle-to-vehicle (V2V) commun...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on cybernetics 2022-11, Vol.52 (11), p.12003-12015
Hauptverfasser: Xiao, Shunyuan, Ge, Xiaohua, Han, Qing-Long, Zhang, Yijun
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 12015
container_issue 11
container_start_page 12003
container_title IEEE transactions on cybernetics
container_volume 52
creator Xiao, Shunyuan
Ge, Xiaohua
Han, Qing-Long
Zhang, Yijun
description This article deals with the problem of secure distributed adaptive platooning control of automated vehicles over vehicular ad-hoc networks (VANETs) in the presence of intermittent denial-of-service (DoS) attacks. The platoon, which is wirelessly connected via directed vehicle-to-vehicle (V2V) communication, is composed of a group of following vehicles subject to unknown heterogeneous nonlinearities and external disturbance inputs, and a leading vehicle subject to unknown nonlinearity and external disturbance as well as an unknown control input. Under such a platoon setting, this article aims to accomplish secure distributed platoon formation tracking with the desired longitudinal spacing and the same velocities and accelerations guided by the leader regardless of the simultaneous presence of nonlinearities, uncertainties, and DoS attacks. First, a new logical data packet processor is developed on each vehicle to identify the intermittent DoS attacks via verifying the time-stamps of the received data packets. Then, a scalable distributed neural-network-based adaptive control design approach is proposed to achieve secure platooning control. It is proved that under the established design procedure, the vehicle state estimation errors and platoon tracking errors can be regulated to reside in small neighborhoods around zero. Finally, comparative simulation studies are provided to substantiate the effectiveness and merits of the proposed control design approach on maintaining the desired platooning performance and attack tolerance.
doi_str_mv 10.1109/TCYB.2021.3074318
format Article
fullrecord <record><control><sourceid>proquest_RIE</sourceid><recordid>TN_cdi_crossref_primary_10_1109_TCYB_2021_3074318</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>9440748</ieee_id><sourcerecordid>2726117183</sourcerecordid><originalsourceid>FETCH-LOGICAL-c326t-455d67b75dfc15dbf3a6b7bbb1621c147a6831e70528d49befba00ee1aadeb9f3</originalsourceid><addsrcrecordid>eNpdkU1P3DAQhq2qVUGUH1D1YqmXXrJ4bCdOjtulBSRUKgGVerJsZ9IasvFiO4s494_j1SIOnct8Pe9opJeQj8AWAKw7uVn9_rrgjMNCMCUFtG_IIYemrThX9dvXulEH5DilO1aiLaOufU8OhGRC1Iofkn_X6OaI9NSnHL2dM_Z02ZtN9lukP0eTQ5j89IeuwpRjGGkY6HLOYW124C_8692IiV5tMe67eTSxHKjOg6M_MD-GeJ_o7dSX_SlO3oxVGKprjFvvkC5zNu4-fSDvBjMmPH7JR-T2-7eb1Xl1eXV2sVpeVk7wJleyrvtGWVX3g4O6t4MwjVXWWmg4OJDKNK0AVKzmbS87i4M1jCGCMT3abhBH5Mv-7iaGhxlT1mufHI6jmTDMSfNacC5BAivo5__QuzDHqXynueINgIJWFAr2lIshpYiD3kS_NvFJA9M7k_TOJL0zSb-YVDSf9hqPiK98J2XZt-IZGQOM4Q</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2726117183</pqid></control><display><type>article</type><title>Secure Distributed Adaptive Platooning Control of Automated Vehicles Over Vehicular Ad-Hoc Networks Under Denial-of-Service Attacks</title><source>IEEE Electronic Library (IEL)</source><creator>Xiao, Shunyuan ; Ge, Xiaohua ; Han, Qing-Long ; Zhang, Yijun</creator><creatorcontrib>Xiao, Shunyuan ; Ge, Xiaohua ; Han, Qing-Long ; Zhang, Yijun</creatorcontrib><description>This article deals with the problem of secure distributed adaptive platooning control of automated vehicles over vehicular ad-hoc networks (VANETs) in the presence of intermittent denial-of-service (DoS) attacks. The platoon, which is wirelessly connected via directed vehicle-to-vehicle (V2V) communication, is composed of a group of following vehicles subject to unknown heterogeneous nonlinearities and external disturbance inputs, and a leading vehicle subject to unknown nonlinearity and external disturbance as well as an unknown control input. Under such a platoon setting, this article aims to accomplish secure distributed platoon formation tracking with the desired longitudinal spacing and the same velocities and accelerations guided by the leader regardless of the simultaneous presence of nonlinearities, uncertainties, and DoS attacks. First, a new logical data packet processor is developed on each vehicle to identify the intermittent DoS attacks via verifying the time-stamps of the received data packets. Then, a scalable distributed neural-network-based adaptive control design approach is proposed to achieve secure platooning control. It is proved that under the established design procedure, the vehicle state estimation errors and platoon tracking errors can be regulated to reside in small neighborhoods around zero. Finally, comparative simulation studies are provided to substantiate the effectiveness and merits of the proposed control design approach on maintaining the desired platooning performance and attack tolerance.</description><identifier>ISSN: 2168-2267</identifier><identifier>EISSN: 2168-2275</identifier><identifier>DOI: 10.1109/TCYB.2021.3074318</identifier><identifier>PMID: 34033572</identifier><identifier>CODEN: ITCEB8</identifier><language>eng</language><publisher>Piscataway: IEEE</publisher><subject>Adaptive control ; Artificial neural networks ; Automated vehicles ; Automatic control ; Automation ; Denial of service attacks ; denial-of-service (DoS) attacks ; Denial-of-service attack ; directed communication topology ; Microprocessors ; Mobile ad hoc networks ; Network topology ; Neural networks ; neural networks (NNs) ; Nonlinearity ; Packets (communication) ; Platooning ; Roads ; secure control ; State estimation ; Topology ; Tracking errors ; Vehicle dynamics ; Vehicles ; Vehicular ad hoc networks ; vehicular ad-hoc network (VANET)</subject><ispartof>IEEE transactions on cybernetics, 2022-11, Vol.52 (11), p.12003-12015</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2022</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c326t-455d67b75dfc15dbf3a6b7bbb1621c147a6831e70528d49befba00ee1aadeb9f3</citedby><cites>FETCH-LOGICAL-c326t-455d67b75dfc15dbf3a6b7bbb1621c147a6831e70528d49befba00ee1aadeb9f3</cites><orcidid>0000-0003-0180-0897 ; 0000-0003-2705-6672 ; 0000-0002-7207-0716 ; 0000-0001-6628-8535</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9440748$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,796,27924,27925,54758</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/9440748$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Xiao, Shunyuan</creatorcontrib><creatorcontrib>Ge, Xiaohua</creatorcontrib><creatorcontrib>Han, Qing-Long</creatorcontrib><creatorcontrib>Zhang, Yijun</creatorcontrib><title>Secure Distributed Adaptive Platooning Control of Automated Vehicles Over Vehicular Ad-Hoc Networks Under Denial-of-Service Attacks</title><title>IEEE transactions on cybernetics</title><addtitle>TCYB</addtitle><description>This article deals with the problem of secure distributed adaptive platooning control of automated vehicles over vehicular ad-hoc networks (VANETs) in the presence of intermittent denial-of-service (DoS) attacks. The platoon, which is wirelessly connected via directed vehicle-to-vehicle (V2V) communication, is composed of a group of following vehicles subject to unknown heterogeneous nonlinearities and external disturbance inputs, and a leading vehicle subject to unknown nonlinearity and external disturbance as well as an unknown control input. Under such a platoon setting, this article aims to accomplish secure distributed platoon formation tracking with the desired longitudinal spacing and the same velocities and accelerations guided by the leader regardless of the simultaneous presence of nonlinearities, uncertainties, and DoS attacks. First, a new logical data packet processor is developed on each vehicle to identify the intermittent DoS attacks via verifying the time-stamps of the received data packets. Then, a scalable distributed neural-network-based adaptive control design approach is proposed to achieve secure platooning control. It is proved that under the established design procedure, the vehicle state estimation errors and platoon tracking errors can be regulated to reside in small neighborhoods around zero. Finally, comparative simulation studies are provided to substantiate the effectiveness and merits of the proposed control design approach on maintaining the desired platooning performance and attack tolerance.</description><subject>Adaptive control</subject><subject>Artificial neural networks</subject><subject>Automated vehicles</subject><subject>Automatic control</subject><subject>Automation</subject><subject>Denial of service attacks</subject><subject>denial-of-service (DoS) attacks</subject><subject>Denial-of-service attack</subject><subject>directed communication topology</subject><subject>Microprocessors</subject><subject>Mobile ad hoc networks</subject><subject>Network topology</subject><subject>Neural networks</subject><subject>neural networks (NNs)</subject><subject>Nonlinearity</subject><subject>Packets (communication)</subject><subject>Platooning</subject><subject>Roads</subject><subject>secure control</subject><subject>State estimation</subject><subject>Topology</subject><subject>Tracking errors</subject><subject>Vehicle dynamics</subject><subject>Vehicles</subject><subject>Vehicular ad hoc networks</subject><subject>vehicular ad-hoc network (VANET)</subject><issn>2168-2267</issn><issn>2168-2275</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpdkU1P3DAQhq2qVUGUH1D1YqmXXrJ4bCdOjtulBSRUKgGVerJsZ9IasvFiO4s494_j1SIOnct8Pe9opJeQj8AWAKw7uVn9_rrgjMNCMCUFtG_IIYemrThX9dvXulEH5DilO1aiLaOufU8OhGRC1Iofkn_X6OaI9NSnHL2dM_Z02ZtN9lukP0eTQ5j89IeuwpRjGGkY6HLOYW124C_8692IiV5tMe67eTSxHKjOg6M_MD-GeJ_o7dSX_SlO3oxVGKprjFvvkC5zNu4-fSDvBjMmPH7JR-T2-7eb1Xl1eXV2sVpeVk7wJleyrvtGWVX3g4O6t4MwjVXWWmg4OJDKNK0AVKzmbS87i4M1jCGCMT3abhBH5Mv-7iaGhxlT1mufHI6jmTDMSfNacC5BAivo5__QuzDHqXynueINgIJWFAr2lIshpYiD3kS_NvFJA9M7k_TOJL0zSb-YVDSf9hqPiK98J2XZt-IZGQOM4Q</recordid><startdate>20221101</startdate><enddate>20221101</enddate><creator>Xiao, Shunyuan</creator><creator>Ge, Xiaohua</creator><creator>Han, Qing-Long</creator><creator>Zhang, Yijun</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>7TB</scope><scope>8FD</scope><scope>F28</scope><scope>FR3</scope><scope>H8D</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0003-0180-0897</orcidid><orcidid>https://orcid.org/0000-0003-2705-6672</orcidid><orcidid>https://orcid.org/0000-0002-7207-0716</orcidid><orcidid>https://orcid.org/0000-0001-6628-8535</orcidid></search><sort><creationdate>20221101</creationdate><title>Secure Distributed Adaptive Platooning Control of Automated Vehicles Over Vehicular Ad-Hoc Networks Under Denial-of-Service Attacks</title><author>Xiao, Shunyuan ; Ge, Xiaohua ; Han, Qing-Long ; Zhang, Yijun</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c326t-455d67b75dfc15dbf3a6b7bbb1621c147a6831e70528d49befba00ee1aadeb9f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Adaptive control</topic><topic>Artificial neural networks</topic><topic>Automated vehicles</topic><topic>Automatic control</topic><topic>Automation</topic><topic>Denial of service attacks</topic><topic>denial-of-service (DoS) attacks</topic><topic>Denial-of-service attack</topic><topic>directed communication topology</topic><topic>Microprocessors</topic><topic>Mobile ad hoc networks</topic><topic>Network topology</topic><topic>Neural networks</topic><topic>neural networks (NNs)</topic><topic>Nonlinearity</topic><topic>Packets (communication)</topic><topic>Platooning</topic><topic>Roads</topic><topic>secure control</topic><topic>State estimation</topic><topic>Topology</topic><topic>Tracking errors</topic><topic>Vehicle dynamics</topic><topic>Vehicles</topic><topic>Vehicular ad hoc networks</topic><topic>vehicular ad-hoc network (VANET)</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Xiao, Shunyuan</creatorcontrib><creatorcontrib>Ge, Xiaohua</creatorcontrib><creatorcontrib>Han, Qing-Long</creatorcontrib><creatorcontrib>Zhang, Yijun</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005–Present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics &amp; Communications Abstracts</collection><collection>Mechanical &amp; Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>ANTE: Abstracts in New Technology &amp; Engineering</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>MEDLINE - Academic</collection><jtitle>IEEE transactions on cybernetics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Xiao, Shunyuan</au><au>Ge, Xiaohua</au><au>Han, Qing-Long</au><au>Zhang, Yijun</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Secure Distributed Adaptive Platooning Control of Automated Vehicles Over Vehicular Ad-Hoc Networks Under Denial-of-Service Attacks</atitle><jtitle>IEEE transactions on cybernetics</jtitle><stitle>TCYB</stitle><date>2022-11-01</date><risdate>2022</risdate><volume>52</volume><issue>11</issue><spage>12003</spage><epage>12015</epage><pages>12003-12015</pages><issn>2168-2267</issn><eissn>2168-2275</eissn><coden>ITCEB8</coden><abstract>This article deals with the problem of secure distributed adaptive platooning control of automated vehicles over vehicular ad-hoc networks (VANETs) in the presence of intermittent denial-of-service (DoS) attacks. The platoon, which is wirelessly connected via directed vehicle-to-vehicle (V2V) communication, is composed of a group of following vehicles subject to unknown heterogeneous nonlinearities and external disturbance inputs, and a leading vehicle subject to unknown nonlinearity and external disturbance as well as an unknown control input. Under such a platoon setting, this article aims to accomplish secure distributed platoon formation tracking with the desired longitudinal spacing and the same velocities and accelerations guided by the leader regardless of the simultaneous presence of nonlinearities, uncertainties, and DoS attacks. First, a new logical data packet processor is developed on each vehicle to identify the intermittent DoS attacks via verifying the time-stamps of the received data packets. Then, a scalable distributed neural-network-based adaptive control design approach is proposed to achieve secure platooning control. It is proved that under the established design procedure, the vehicle state estimation errors and platoon tracking errors can be regulated to reside in small neighborhoods around zero. Finally, comparative simulation studies are provided to substantiate the effectiveness and merits of the proposed control design approach on maintaining the desired platooning performance and attack tolerance.</abstract><cop>Piscataway</cop><pub>IEEE</pub><pmid>34033572</pmid><doi>10.1109/TCYB.2021.3074318</doi><tpages>13</tpages><orcidid>https://orcid.org/0000-0003-0180-0897</orcidid><orcidid>https://orcid.org/0000-0003-2705-6672</orcidid><orcidid>https://orcid.org/0000-0002-7207-0716</orcidid><orcidid>https://orcid.org/0000-0001-6628-8535</orcidid></addata></record>
fulltext fulltext_linktorsrc
identifier ISSN: 2168-2267
ispartof IEEE transactions on cybernetics, 2022-11, Vol.52 (11), p.12003-12015
issn 2168-2267
2168-2275
language eng
recordid cdi_crossref_primary_10_1109_TCYB_2021_3074318
source IEEE Electronic Library (IEL)
subjects Adaptive control
Artificial neural networks
Automated vehicles
Automatic control
Automation
Denial of service attacks
denial-of-service (DoS) attacks
Denial-of-service attack
directed communication topology
Microprocessors
Mobile ad hoc networks
Network topology
Neural networks
neural networks (NNs)
Nonlinearity
Packets (communication)
Platooning
Roads
secure control
State estimation
Topology
Tracking errors
Vehicle dynamics
Vehicles
Vehicular ad hoc networks
vehicular ad-hoc network (VANET)
title Secure Distributed Adaptive Platooning Control of Automated Vehicles Over Vehicular Ad-Hoc Networks Under Denial-of-Service Attacks
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-25T11%3A28%3A33IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_RIE&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Secure%20Distributed%20Adaptive%20Platooning%20Control%20of%20Automated%20Vehicles%20Over%20Vehicular%20Ad-Hoc%20Networks%20Under%20Denial-of-Service%20Attacks&rft.jtitle=IEEE%20transactions%20on%20cybernetics&rft.au=Xiao,%20Shunyuan&rft.date=2022-11-01&rft.volume=52&rft.issue=11&rft.spage=12003&rft.epage=12015&rft.pages=12003-12015&rft.issn=2168-2267&rft.eissn=2168-2275&rft.coden=ITCEB8&rft_id=info:doi/10.1109/TCYB.2021.3074318&rft_dat=%3Cproquest_RIE%3E2726117183%3C/proquest_RIE%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2726117183&rft_id=info:pmid/34033572&rft_ieee_id=9440748&rfr_iscdi=true