A malware detection system inspired on the human immune system

Detalhes bibliográficos
Autor(a) principal: De Oliveira, Isabela Liane [UNESP]
Data de Publicação: 2012
Outros Autores: Grégio, André Ricardo Abed, Cansian, Adriano Mauro [UNESP]
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1007/978-3-642-31128-4_21
http://hdl.handle.net/11449/73443
Resumo: Malicious programs (malware) can cause severe damage on computer systems and data. The mechanism that the human immune system uses to detect and protect from organisms that threaten the human body is efficient and can be adapted to detect malware attacks. In this paper we propose a system to perform malware distributed collection, analysis and detection, this last inspired by the human immune system. After collecting malware samples from Internet, they are dynamically analyzed so as to provide execution traces at the operating system level and network flows that are used to create a behavioral model and to generate a detection signature. Those signatures serve as input to a malware detector, acting as the antibodies in the antigen detection process. This allows us to understand the malware attack and aids in the infection removal procedures. © 2012 Springer-Verlag.
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spelling A malware detection system inspired on the human immune systemdata mininghuman immune systemmalicious codeAntigen detectionsBehavioral modelExecution traceHuman bodiesHuman immune systemsMalicious codesMalware attacksMalware detectionMalwaresNetwork flowsChemical detectionComputer aided network analysisComputer crimeData miningDetectorsNetwork securityImmunologyMalicious programs (malware) can cause severe damage on computer systems and data. The mechanism that the human immune system uses to detect and protect from organisms that threaten the human body is efficient and can be adapted to detect malware attacks. In this paper we propose a system to perform malware distributed collection, analysis and detection, this last inspired by the human immune system. After collecting malware samples from Internet, they are dynamically analyzed so as to provide execution traces at the operating system level and network flows that are used to create a behavioral model and to generate a detection signature. Those signatures serve as input to a malware detector, acting as the antibodies in the antigen detection process. This allows us to understand the malware attack and aids in the infection removal procedures. © 2012 Springer-Verlag.São Paulo State University (Unesp), São José do Rio Preto, SPRenato Archer IT Research Center (CTI/MCT), Campinas, SPSão Paulo State University (Unesp), São José do Rio Preto, SPUniversidade Estadual Paulista (Unesp)Renato Archer IT Research Center (CTI/MCT)De Oliveira, Isabela Liane [UNESP]Grégio, André Ricardo AbedCansian, Adriano Mauro [UNESP]2014-05-27T11:26:53Z2014-05-27T11:26:53Z2012-07-23info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject286-301http://dx.doi.org/10.1007/978-3-642-31128-4_21Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 7336 LNCS, n. PART 4, p. 286-301, 2012.0302-97431611-3349http://hdl.handle.net/11449/7344310.1007/978-3-642-31128-4_21WOS:0003082897000212-s2.0-8486394077400959219433459740000-0003-4494-1454Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)0,295info:eu-repo/semantics/openAccess2021-10-23T21:44:33Zoai:repositorio.unesp.br:11449/73443Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T22:44:43.658893Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv A malware detection system inspired on the human immune system
title A malware detection system inspired on the human immune system
spellingShingle A malware detection system inspired on the human immune system
De Oliveira, Isabela Liane [UNESP]
data mining
human immune system
malicious code
Antigen detections
Behavioral model
Execution trace
Human bodies
Human immune systems
Malicious codes
Malware attacks
Malware detection
Malwares
Network flows
Chemical detection
Computer aided network analysis
Computer crime
Data mining
Detectors
Network security
Immunology
title_short A malware detection system inspired on the human immune system
title_full A malware detection system inspired on the human immune system
title_fullStr A malware detection system inspired on the human immune system
title_full_unstemmed A malware detection system inspired on the human immune system
title_sort A malware detection system inspired on the human immune system
author De Oliveira, Isabela Liane [UNESP]
author_facet De Oliveira, Isabela Liane [UNESP]
Grégio, André Ricardo Abed
Cansian, Adriano Mauro [UNESP]
author_role author
author2 Grégio, André Ricardo Abed
Cansian, Adriano Mauro [UNESP]
author2_role author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
Renato Archer IT Research Center (CTI/MCT)
dc.contributor.author.fl_str_mv De Oliveira, Isabela Liane [UNESP]
Grégio, André Ricardo Abed
Cansian, Adriano Mauro [UNESP]
dc.subject.por.fl_str_mv data mining
human immune system
malicious code
Antigen detections
Behavioral model
Execution trace
Human bodies
Human immune systems
Malicious codes
Malware attacks
Malware detection
Malwares
Network flows
Chemical detection
Computer aided network analysis
Computer crime
Data mining
Detectors
Network security
Immunology
topic data mining
human immune system
malicious code
Antigen detections
Behavioral model
Execution trace
Human bodies
Human immune systems
Malicious codes
Malware attacks
Malware detection
Malwares
Network flows
Chemical detection
Computer aided network analysis
Computer crime
Data mining
Detectors
Network security
Immunology
description Malicious programs (malware) can cause severe damage on computer systems and data. The mechanism that the human immune system uses to detect and protect from organisms that threaten the human body is efficient and can be adapted to detect malware attacks. In this paper we propose a system to perform malware distributed collection, analysis and detection, this last inspired by the human immune system. After collecting malware samples from Internet, they are dynamically analyzed so as to provide execution traces at the operating system level and network flows that are used to create a behavioral model and to generate a detection signature. Those signatures serve as input to a malware detector, acting as the antibodies in the antigen detection process. This allows us to understand the malware attack and aids in the infection removal procedures. © 2012 Springer-Verlag.
publishDate 2012
dc.date.none.fl_str_mv 2012-07-23
2014-05-27T11:26:53Z
2014-05-27T11:26:53Z
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/10.1007/978-3-642-31128-4_21
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 7336 LNCS, n. PART 4, p. 286-301, 2012.
0302-9743
1611-3349
http://hdl.handle.net/11449/73443
10.1007/978-3-642-31128-4_21
WOS:000308289700021
2-s2.0-84863940774
0095921943345974
0000-0003-4494-1454
url http://dx.doi.org/10.1007/978-3-642-31128-4_21
http://hdl.handle.net/11449/73443
identifier_str_mv Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 7336 LNCS, n. PART 4, p. 286-301, 2012.
0302-9743
1611-3349
10.1007/978-3-642-31128-4_21
WOS:000308289700021
2-s2.0-84863940774
0095921943345974
0000-0003-4494-1454
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
0,295
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 286-301
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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