Data mining the memory access stream to detect anomalous application behavior
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Outros Autores: | , , |
Tipo de documento: | Artigo de conferência |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFRGS |
Texto Completo: | http://hdl.handle.net/10183/159015 |
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Moreira, Francis BirckNavaux, Philippe Olivier AlexandreDiener, MatthiasKoren, Israel2017-06-02T02:42:36Z2017http://hdl.handle.net/10183/159015001023031application/pdfengACM International Conference on Computing Frontier ( 2017 May 15-17 : Siena, Italy). Proceedings. New York : ACM, c2017Tolerancia : FalhasMemoria : ComputadoresEngenharia : SoftwareMemory access patternsMachine learningSingle bit flipsData mining the memory access stream to detect anomalous application behaviorEstrangeiroinfo:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFRGSinstname:Universidade Federal do Rio Grande do Sul (UFRGS)instacron:UFRGSORIGINAL001023031.pdf001023031.pdfTexto completo (inglês)application/pdf628460http://www.lume.ufrgs.br/bitstream/10183/159015/1/001023031.pdfdc664676fa6917520cf049f91c9430deMD51TEXT001023031.pdf.txt001023031.pdf.txtExtracted Texttext/plain46104http://www.lume.ufrgs.br/bitstream/10183/159015/2/001023031.pdf.txt5c357f699258557c2e7e82855c950b65MD5210183/1590152017-06-03 02:43:29.236148oai:www.lume.ufrgs.br:10183/159015Repositório InstitucionalPUBhttps://lume.ufrgs.br/oai/requestlume@ufrgs.bropendoar:2017-06-03T05:43:29Repositório Institucional da UFRGS - Universidade Federal do Rio Grande do Sul (UFRGS)false |
dc.title.pt_BR.fl_str_mv |
Data mining the memory access stream to detect anomalous application behavior |
title |
Data mining the memory access stream to detect anomalous application behavior |
spellingShingle |
Data mining the memory access stream to detect anomalous application behavior Moreira, Francis Birck Tolerancia : Falhas Memoria : Computadores Engenharia : Software Memory access patterns Machine learning Single bit flips |
title_short |
Data mining the memory access stream to detect anomalous application behavior |
title_full |
Data mining the memory access stream to detect anomalous application behavior |
title_fullStr |
Data mining the memory access stream to detect anomalous application behavior |
title_full_unstemmed |
Data mining the memory access stream to detect anomalous application behavior |
title_sort |
Data mining the memory access stream to detect anomalous application behavior |
author |
Moreira, Francis Birck |
author_facet |
Moreira, Francis Birck Navaux, Philippe Olivier Alexandre Diener, Matthias Koren, Israel |
author_role |
author |
author2 |
Navaux, Philippe Olivier Alexandre Diener, Matthias Koren, Israel |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Moreira, Francis Birck Navaux, Philippe Olivier Alexandre Diener, Matthias Koren, Israel |
dc.subject.por.fl_str_mv |
Tolerancia : Falhas Memoria : Computadores Engenharia : Software |
topic |
Tolerancia : Falhas Memoria : Computadores Engenharia : Software Memory access patterns Machine learning Single bit flips |
dc.subject.eng.fl_str_mv |
Memory access patterns Machine learning Single bit flips |
publishDate |
2017 |
dc.date.accessioned.fl_str_mv |
2017-06-02T02:42:36Z |
dc.date.issued.fl_str_mv |
2017 |
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Estrangeiro info:eu-repo/semantics/conferenceObject |
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info:eu-repo/semantics/publishedVersion |
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conferenceObject |
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http://hdl.handle.net/10183/159015 |
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001023031 |
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http://hdl.handle.net/10183/159015 |
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eng |
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eng |
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ACM International Conference on Computing Frontier ( 2017 May 15-17 : Siena, Italy). Proceedings. New York : ACM, c2017 |
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