Detecting time-fragmented cache attacks against AES using Performance Monitoring Counters

Autores
Prada, Iván; Igual, Francisco D.; Olcoz Herrero, Katzalin
Año de publicación
2019
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Cache timing attacks use shared caches in multi-core processors as side channels to extract information from victim processes. These attacks are particularly dangerous in cloud infrastructures, in which the deployed countermeasures cause collateral e ects in terms of performance loss and increase in energy consumption. We propose to monitor the victim process using an independent monitoring (detector) process, that continuously measures selected Performance Monitoring Counters (PMC) to detect the presence of an attack. Ad-hoc counter- measures can be applied only when such a risky situation arises. In our case, the victim process is the Advanced Encryption Standard (AES) encryption algorithm and the attack is performed by means of random encryption requests. We demonstrate that PMCs are a feasible tool to detect the attack and that sampling PMCs at high frequencies is worse than sampling at lower frequencies in terms of detection capabilities, particularly when the attack is fragmented in time to try to be hidden from detection.
Instituto de Investigación en Informática
Materia
Ciencias Informáticas
cache attacks
flush+reload
AES
performance monitoring counters
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/80337

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spelling Detecting time-fragmented cache attacks against AES using Performance Monitoring CountersPrada, IvánIgual, Francisco D.Olcoz Herrero, KatzalinCiencias Informáticascache attacksflush+reloadAESperformance monitoring countersCache timing attacks use shared caches in multi-core processors as side channels to extract information from victim processes. These attacks are particularly dangerous in cloud infrastructures, in which the deployed countermeasures cause collateral e ects in terms of performance loss and increase in energy consumption. We propose to monitor the victim process using an independent monitoring (detector) process, that continuously measures selected Performance Monitoring Counters (PMC) to detect the presence of an attack. Ad-hoc counter- measures can be applied only when such a risky situation arises. In our case, the victim process is the Advanced Encryption Standard (AES) encryption algorithm and the attack is performed by means of random encryption requests. We demonstrate that PMCs are a feasible tool to detect the attack and that sampling PMCs at high frequencies is worse than sampling at lower frequencies in terms of detection capabilities, particularly when the attack is fragmented in time to try to be hidden from detection.Instituto de Investigación en Informática2019-06info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf3-15http://sedici.unlp.edu.ar/handle/10915/80337enginfo:eu-repo/semantics/altIdentifier/isbn/978-3-030-27713-0info:eu-repo/semantics/reference/doi/10.1007/978-3-030-27713-0info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-10-15T11:06:43Zoai:sedici.unlp.edu.ar:10915/80337Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-10-15 11:06:43.66SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Detecting time-fragmented cache attacks against AES using Performance Monitoring Counters
title Detecting time-fragmented cache attacks against AES using Performance Monitoring Counters
spellingShingle Detecting time-fragmented cache attacks against AES using Performance Monitoring Counters
Prada, Iván
Ciencias Informáticas
cache attacks
flush+reload
AES
performance monitoring counters
title_short Detecting time-fragmented cache attacks against AES using Performance Monitoring Counters
title_full Detecting time-fragmented cache attacks against AES using Performance Monitoring Counters
title_fullStr Detecting time-fragmented cache attacks against AES using Performance Monitoring Counters
title_full_unstemmed Detecting time-fragmented cache attacks against AES using Performance Monitoring Counters
title_sort Detecting time-fragmented cache attacks against AES using Performance Monitoring Counters
dc.creator.none.fl_str_mv Prada, Iván
Igual, Francisco D.
Olcoz Herrero, Katzalin
author Prada, Iván
author_facet Prada, Iván
Igual, Francisco D.
Olcoz Herrero, Katzalin
author_role author
author2 Igual, Francisco D.
Olcoz Herrero, Katzalin
author2_role author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
cache attacks
flush+reload
AES
performance monitoring counters
topic Ciencias Informáticas
cache attacks
flush+reload
AES
performance monitoring counters
dc.description.none.fl_txt_mv Cache timing attacks use shared caches in multi-core processors as side channels to extract information from victim processes. These attacks are particularly dangerous in cloud infrastructures, in which the deployed countermeasures cause collateral e ects in terms of performance loss and increase in energy consumption. We propose to monitor the victim process using an independent monitoring (detector) process, that continuously measures selected Performance Monitoring Counters (PMC) to detect the presence of an attack. Ad-hoc counter- measures can be applied only when such a risky situation arises. In our case, the victim process is the Advanced Encryption Standard (AES) encryption algorithm and the attack is performed by means of random encryption requests. We demonstrate that PMCs are a feasible tool to detect the attack and that sampling PMCs at high frequencies is worse than sampling at lower frequencies in terms of detection capabilities, particularly when the attack is fragmented in time to try to be hidden from detection.
Instituto de Investigación en Informática
description Cache timing attacks use shared caches in multi-core processors as side channels to extract information from victim processes. These attacks are particularly dangerous in cloud infrastructures, in which the deployed countermeasures cause collateral e ects in terms of performance loss and increase in energy consumption. We propose to monitor the victim process using an independent monitoring (detector) process, that continuously measures selected Performance Monitoring Counters (PMC) to detect the presence of an attack. Ad-hoc counter- measures can be applied only when such a risky situation arises. In our case, the victim process is the Advanced Encryption Standard (AES) encryption algorithm and the attack is performed by means of random encryption requests. We demonstrate that PMCs are a feasible tool to detect the attack and that sampling PMCs at high frequencies is worse than sampling at lower frequencies in terms of detection capabilities, particularly when the attack is fragmented in time to try to be hidden from detection.
publishDate 2019
dc.date.none.fl_str_mv 2019-06
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dc.language.none.fl_str_mv eng
language eng
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info:eu-repo/semantics/reference/doi/10.1007/978-3-030-27713-0
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
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