DDoS attack detection mechanism in the application layer using user features

Descripción del Articulo

The authors thank the National Council of Science,Technology and Technological Innovation (CONCYTEC)-Peru and Technical University of Cotopaxi for the partial funding of this work and Professor Angel H. Moreno for their contributions to this work
Detalles Bibliográficos
Autores: Bravo S., Mauricio D.
Formato: objeto de conferencia
Fecha de Publicación:2018
Institución:Consejo Nacional de Ciencia Tecnología e Innovación
Repositorio:CONCYTEC-Institucional
Lenguaje:inglés
OAI Identifier:oai:repositorio.concytec.gob.pe:20.500.12390/545
Enlace del recurso:https://hdl.handle.net/20.500.12390/545
https://doi.org/10.1109/INFOCT.2018.8356848
Nivel de acceso:acceso abierto
Materia:Websites
Network layers
Application layers
DDoS
Detection approach
Detection efficiency
Detection of attacks
dynamism user
features user
Denial-of-service attack
https://purl.org/pe-repo/ocde/ford#1.02.01
id CONC_7efc1303de1123a473b7d0022110f608
oai_identifier_str oai:repositorio.concytec.gob.pe:20.500.12390/545
network_acronym_str CONC
network_name_str CONCYTEC-Institucional
repository_id_str 4689
dc.title.none.fl_str_mv DDoS attack detection mechanism in the application layer using user features
title DDoS attack detection mechanism in the application layer using user features
spellingShingle DDoS attack detection mechanism in the application layer using user features
Bravo S.
Websites
Network layers
Application layers
DDoS
Detection approach
Detection efficiency
Detection of attacks
dynamism user
features user
Denial-of-service attack
https://purl.org/pe-repo/ocde/ford#1.02.01
title_short DDoS attack detection mechanism in the application layer using user features
title_full DDoS attack detection mechanism in the application layer using user features
title_fullStr DDoS attack detection mechanism in the application layer using user features
title_full_unstemmed DDoS attack detection mechanism in the application layer using user features
title_sort DDoS attack detection mechanism in the application layer using user features
author Bravo S.
author_facet Bravo S.
Mauricio D.
author_role author
author2 Mauricio D.
author2_role author
dc.contributor.author.fl_str_mv Bravo S.
Mauricio D.
dc.subject.none.fl_str_mv Websites
topic Websites
Network layers
Application layers
DDoS
Detection approach
Detection efficiency
Detection of attacks
dynamism user
features user
Denial-of-service attack
https://purl.org/pe-repo/ocde/ford#1.02.01
dc.subject.es_PE.fl_str_mv Network layers
Application layers
DDoS
Detection approach
Detection efficiency
Detection of attacks
dynamism user
features user
Denial-of-service attack
dc.subject.ocde.none.fl_str_mv https://purl.org/pe-repo/ocde/ford#1.02.01
description The authors thank the National Council of Science,Technology and Technological Innovation (CONCYTEC)-Peru and Technical University of Cotopaxi for the partial funding of this work and Professor Angel H. Moreno for their contributions to this work
publishDate 2018
dc.date.accessioned.none.fl_str_mv 2024-05-30T23:13:38Z
dc.date.available.none.fl_str_mv 2024-05-30T23:13:38Z
dc.date.issued.fl_str_mv 2018
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
format conferenceObject
dc.identifier.isbn.none.fl_str_mv 9781538653845
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12390/545
dc.identifier.doi.none.fl_str_mv https://doi.org/10.1109/INFOCT.2018.8356848
dc.identifier.scopus.none.fl_str_mv 2-s2.0-85048376703
identifier_str_mv 9781538653845
2-s2.0-85048376703
url https://hdl.handle.net/20.500.12390/545
https://doi.org/10.1109/INFOCT.2018.8356848
dc.language.iso.none.fl_str_mv eng
language eng
dc.relation.ispartof.none.fl_str_mv 2018 International Conference on Information and Computer Technologies, ICICT 2018
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers Inc.
publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers Inc.
dc.source.none.fl_str_mv reponame:CONCYTEC-Institucional
instname:Consejo Nacional de Ciencia Tecnología e Innovación
instacron:CONCYTEC
instname_str Consejo Nacional de Ciencia Tecnología e Innovación
instacron_str CONCYTEC
institution CONCYTEC
reponame_str CONCYTEC-Institucional
collection CONCYTEC-Institucional
repository.name.fl_str_mv Repositorio Institucional CONCYTEC
repository.mail.fl_str_mv repositorio@concytec.gob.pe
_version_ 1854395800159780864
spelling Publicationrp00948600rp00949600Bravo S.Mauricio D.2024-05-30T23:13:38Z2024-05-30T23:13:38Z20189781538653845https://hdl.handle.net/20.500.12390/545https://doi.org/10.1109/INFOCT.2018.83568482-s2.0-85048376703The authors thank the National Council of Science,Technology and Technological Innovation (CONCYTEC)-Peru and Technical University of Cotopaxi for the partial funding of this work and Professor Angel H. Moreno for their contributions to this workDDoS attacks are one of the most damaging computer aggressions of recent times. Attackers send large number of requests to saturate a victim machine and it stops providing its services to legitimate users. In general attacks are directed to the network layer and the application layer, the latter has been increasing due mainly to its easy execution and difficult detection. The present work proposes a low cost detection approach that uses the characteristics of the Web User for the detection of attacks. To do this, the features are extracted in real time using functions designed in PHP and JavaScript. They are evaluated by an order 1 classifier to differentiate a real user from a DDoS attack. A real user is identified by making requests interacting with the computer system, while DDoS attacks are requests sent by robots to overload the system with indiscriminate requests. The tests were executed on a computer system using requests from real users and attacks using the LOIC, OWASP and GoldenEye tools. The results show that the proposed method has a detection efficiency of 100%, and that the characteristics of the web user allow to differentiate between a real user and a robot.Consejo Nacional de Ciencia, Tecnología e Innovación Tecnológica - ConcytecengInstitute of Electrical and Electronics Engineers Inc.2018 International Conference on Information and Computer Technologies, ICICT 2018info:eu-repo/semantics/openAccessWebsitesNetwork layers-1Application layers-1DDoS-1Detection approach-1Detection efficiency-1Detection of attacks-1dynamism user-1features user-1Denial-of-service attack-1https://purl.org/pe-repo/ocde/ford#1.02.01-1DDoS attack detection mechanism in the application layer using user featuresinfo:eu-repo/semantics/conferenceObjectreponame:CONCYTEC-Institucionalinstname:Consejo Nacional de Ciencia Tecnología e Innovacióninstacron:CONCYTEC#PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE#20.500.12390/545oai:repositorio.concytec.gob.pe:20.500.12390/5452024-05-30 15:35:42.919http://purl.org/coar/access_right/c_14cbinfo:eu-repo/semantics/closedAccessmetadata only accesshttps://repositorio.concytec.gob.peRepositorio Institucional CONCYTECrepositorio@concytec.gob.pe#PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE#<Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="91dcfb64-9901-40e9-9f85-267ec3509f55"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>DDoS attack detection mechanism in the application layer using user features</Title> <PublishedIn> <Publication> <Title>2018 International Conference on Information and Computer Technologies, ICICT 2018</Title> </Publication> </PublishedIn> <PublicationDate>2018</PublicationDate> <DOI>https://doi.org/10.1109/INFOCT.2018.8356848</DOI> <SCP-Number>2-s2.0-85048376703</SCP-Number> <ISBN>9781538653845</ISBN> <Authors> <Author> <DisplayName>Bravo S.</DisplayName> <Person id="rp00948" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Mauricio D.</DisplayName> <Person id="rp00949" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Institute of Electrical and Electronics Engineers Inc.</DisplayName> <OrgUnit /> </Publisher> </Publishers> <Keyword>Websites</Keyword> <Keyword>Network layers</Keyword> <Keyword>Application layers</Keyword> <Keyword>DDoS</Keyword> <Keyword>Detection approach</Keyword> <Keyword>Detection efficiency</Keyword> <Keyword>Detection of attacks</Keyword> <Keyword>dynamism user</Keyword> <Keyword>features user</Keyword> <Keyword>Denial-of-service attack</Keyword> <Abstract>DDoS attacks are one of the most damaging computer aggressions of recent times. Attackers send large number of requests to saturate a victim machine and it stops providing its services to legitimate users. In general attacks are directed to the network layer and the application layer, the latter has been increasing due mainly to its easy execution and difficult detection. The present work proposes a low cost detection approach that uses the characteristics of the Web User for the detection of attacks. To do this, the features are extracted in real time using functions designed in PHP and JavaScript. They are evaluated by an order 1 classifier to differentiate a real user from a DDoS attack. A real user is identified by making requests interacting with the computer system, while DDoS attacks are requests sent by robots to overload the system with indiscriminate requests. The tests were executed on a computer system using requests from real users and attacks using the LOIC, OWASP and GoldenEye tools. The results show that the proposed method has a detection efficiency of 100%, and that the characteristics of the web user allow to differentiate between a real user and a robot.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication> -1
score 13.944067
DDoS attack detection mechanism in the application layer using user features
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La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).

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