An Attacks Detection Mechanism for Intelligent Transport System
Main Author: | |
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Publication Date: | 2020 |
Other Authors: | , , , , , , , , , , , , , |
Format: | Conference object |
Language: | eng |
Source: | Repositório Institucional da UNESP |
Download full: | http://dx.doi.org/10.1109/BigData50022.2020.9378309 http://hdl.handle.net/11449/218271 |
Summary: | The increase in computational technologies for means of transport, especially vehicles, has provided great benefits through Intelligent Transport Systems (ITS). Drivers, passengers, and pedestrians rely on computer applications that aim to protect human life, including agility in handling emergencies, improvements in traffic, and even leisure and entertainment resources. Communication and data exchange are from vehicles to vehicles (V2V) and from vehicles to road infrastructures (V2I) being carried out through the architecture of the vehicular ad hoc network (VANET). However, this type of network differs from traditional ones, as it operates in a highly dynamic environment, originated by the rapid mobility between its nodes and with short connection intervals. Wireless vehicle communication adopts the IEEE 802.11p standard, allowing vehicles to operate outside a basic set of services. Given these characteristics, numerous threats, vulnerabilities, and denial of service attacks can occur. Prioritizing the safety of life and protecting VANET against this type of attack, a security mechanism is proposed. The mechanism works to detect anomalies through a simple and robust statistical model in the search for extreme values (outliers). Median Absolute Deviation detects large amounts of MAC frames and ARP requests, characteristics of DoS / DDoS from malicious vehicles. Through extensive stages of simulations using the NS-3 and SUMO simulators, the mechanism showed excellent efficiency in detection rates and minimum rates of false positives and false negatives. |
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An Attacks Detection Mechanism for Intelligent Transport SystemIntelligent Transport SystemsVANETinformation securityintrusion detection systemdenial of serviceThe increase in computational technologies for means of transport, especially vehicles, has provided great benefits through Intelligent Transport Systems (ITS). Drivers, passengers, and pedestrians rely on computer applications that aim to protect human life, including agility in handling emergencies, improvements in traffic, and even leisure and entertainment resources. Communication and data exchange are from vehicles to vehicles (V2V) and from vehicles to road infrastructures (V2I) being carried out through the architecture of the vehicular ad hoc network (VANET). However, this type of network differs from traditional ones, as it operates in a highly dynamic environment, originated by the rapid mobility between its nodes and with short connection intervals. Wireless vehicle communication adopts the IEEE 802.11p standard, allowing vehicles to operate outside a basic set of services. Given these characteristics, numerous threats, vulnerabilities, and denial of service attacks can occur. Prioritizing the safety of life and protecting VANET against this type of attack, a security mechanism is proposed. The mechanism works to detect anomalies through a simple and robust statistical model in the search for extreme values (outliers). Median Absolute Deviation detects large amounts of MAC frames and ARP requests, characteristics of DoS / DDoS from malicious vehicles. Through extensive stages of simulations using the NS-3 and SUMO simulators, the mechanism showed excellent efficiency in detection rates and minimum rates of false positives and false negatives.Univ Estadual Paulista, UNESP, Sao Jose Do Rio Preto, BrazilUniv Sao Paulo, Inst Math & Comp Sci ICMC, Sao Carlos, BrazilClemson Univ, Sch Comp, Clemson, SC 29634 USAUniv Estadual Paulista, UNESP, Sao Jose Do Rio Preto, BrazilIeeeUniversidade Estadual Paulista (UNESP)Universidade de São Paulo (USP)Clemson UnivValentini, Edivaldo Pastori [UNESP]Meneguette, Rodolfo IpolitoAlsuhaim, AdilWu, X. T.Jermaine, C.Xiong, L.Hu, X. H.Kotevska, O.Lu, S. Y.Xu, W. J.Aluru, S.Zhai, C. X.Al-Masri, E.Chen, Z. Y.Saltz, J.2022-04-28T17:20:11Z2022-04-28T17:20:11Z2020-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject2453-2461http://dx.doi.org/10.1109/BigData50022.2020.93783092020 Ieee International Conference On Big Data (big Data). New York: Ieee, p. 2453-2461, 2020.2639-1589http://hdl.handle.net/11449/21827110.1109/BigData50022.2020.9378309WOS:000662554702073Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPeng2020 Ieee International Conference On Big Data (big Data)info:eu-repo/semantics/openAccess2022-04-28T17:20:11Zoai:repositorio.unesp.br:11449/218271Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462022-04-28T17:20:11Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
An Attacks Detection Mechanism for Intelligent Transport System |
title |
An Attacks Detection Mechanism for Intelligent Transport System |
spellingShingle |
An Attacks Detection Mechanism for Intelligent Transport System Valentini, Edivaldo Pastori [UNESP] Intelligent Transport Systems VANET information security intrusion detection system denial of service |
title_short |
An Attacks Detection Mechanism for Intelligent Transport System |
title_full |
An Attacks Detection Mechanism for Intelligent Transport System |
title_fullStr |
An Attacks Detection Mechanism for Intelligent Transport System |
title_full_unstemmed |
An Attacks Detection Mechanism for Intelligent Transport System |
title_sort |
An Attacks Detection Mechanism for Intelligent Transport System |
author |
Valentini, Edivaldo Pastori [UNESP] |
author_facet |
Valentini, Edivaldo Pastori [UNESP] Meneguette, Rodolfo Ipolito Alsuhaim, Adil Wu, X. T. Jermaine, C. Xiong, L. Hu, X. H. Kotevska, O. Lu, S. Y. Xu, W. J. Aluru, S. Zhai, C. X. Al-Masri, E. Chen, Z. Y. Saltz, J. |
author_role |
author |
author2 |
Meneguette, Rodolfo Ipolito Alsuhaim, Adil Wu, X. T. Jermaine, C. Xiong, L. Hu, X. H. Kotevska, O. Lu, S. Y. Xu, W. J. Aluru, S. Zhai, C. X. Al-Masri, E. Chen, Z. Y. Saltz, J. |
author2_role |
author author author author author author author author author author author author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (UNESP) Universidade de São Paulo (USP) Clemson Univ |
dc.contributor.author.fl_str_mv |
Valentini, Edivaldo Pastori [UNESP] Meneguette, Rodolfo Ipolito Alsuhaim, Adil Wu, X. T. Jermaine, C. Xiong, L. Hu, X. H. Kotevska, O. Lu, S. Y. Xu, W. J. Aluru, S. Zhai, C. X. Al-Masri, E. Chen, Z. Y. Saltz, J. |
dc.subject.por.fl_str_mv |
Intelligent Transport Systems VANET information security intrusion detection system denial of service |
topic |
Intelligent Transport Systems VANET information security intrusion detection system denial of service |
description |
The increase in computational technologies for means of transport, especially vehicles, has provided great benefits through Intelligent Transport Systems (ITS). Drivers, passengers, and pedestrians rely on computer applications that aim to protect human life, including agility in handling emergencies, improvements in traffic, and even leisure and entertainment resources. Communication and data exchange are from vehicles to vehicles (V2V) and from vehicles to road infrastructures (V2I) being carried out through the architecture of the vehicular ad hoc network (VANET). However, this type of network differs from traditional ones, as it operates in a highly dynamic environment, originated by the rapid mobility between its nodes and with short connection intervals. Wireless vehicle communication adopts the IEEE 802.11p standard, allowing vehicles to operate outside a basic set of services. Given these characteristics, numerous threats, vulnerabilities, and denial of service attacks can occur. Prioritizing the safety of life and protecting VANET against this type of attack, a security mechanism is proposed. The mechanism works to detect anomalies through a simple and robust statistical model in the search for extreme values (outliers). Median Absolute Deviation detects large amounts of MAC frames and ARP requests, characteristics of DoS / DDoS from malicious vehicles. Through extensive stages of simulations using the NS-3 and SUMO simulators, the mechanism showed excellent efficiency in detection rates and minimum rates of false positives and false negatives. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-01-01 2022-04-28T17:20:11Z 2022-04-28T17:20:11Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/conferenceObject |
format |
conferenceObject |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1109/BigData50022.2020.9378309 2020 Ieee International Conference On Big Data (big Data). New York: Ieee, p. 2453-2461, 2020. 2639-1589 http://hdl.handle.net/11449/218271 10.1109/BigData50022.2020.9378309 WOS:000662554702073 |
url |
http://dx.doi.org/10.1109/BigData50022.2020.9378309 http://hdl.handle.net/11449/218271 |
identifier_str_mv |
2020 Ieee International Conference On Big Data (big Data). New York: Ieee, p. 2453-2461, 2020. 2639-1589 10.1109/BigData50022.2020.9378309 WOS:000662554702073 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
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2020 Ieee International Conference On Big Data (big Data) |
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info:eu-repo/semantics/openAccess |
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openAccess |
dc.format.none.fl_str_mv |
2453-2461 |
dc.publisher.none.fl_str_mv |
Ieee |
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Ieee |
dc.source.none.fl_str_mv |
Web of Science reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
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UNESP |
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Repositório Institucional da UNESP |
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Repositório Institucional da UNESP |
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Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
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