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An efficient cache-based access anomaly detection scheme

Authors:

Sang L. Min,

Jong-Deok ChoiAuthors Info & Claims

ACM SIGOPS Operating Systems Review, Volume 25, Issue Special Issue

Pages 235 - 244

https://doi.org/10.1145/106974.106996

Published: 01 April 1991 Publication History

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Cited By

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Armaly AMcMillan C(2016)Pragmatic source code reuse via execution record and replayJournal of Software: Evolution and Process10.1002/smr.179028:8(642-664)Online publication date: 10-May-2016
https://doi.org/10.1002/smr.1790
Kidd NReps TDolby JVaziri M(2011)Finding concurrency-related bugs using random isolationInternational Journal on Software Tools for Technology Transfer10.1007/s10009-011-0197-713:6(495-518)Online publication date: 23-Apr-2011
https://doi.org/10.1007/s10009-011-0197-7
Jun YMcDowell C(2000)Scalable Monitoring Technique for Detecting Races in Parallel ProgramsParallel and Distributed Processing10.1007/3-540-45591-4_44(340-347)Online publication date: 25-May-2000
https://doi.org/10.1007/3-540-45591-4_44
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Index Terms

An efficient cache-based access anomaly detection scheme
1. Computing methodologies
  1. Parallel computing methodologies
    1. Parallel programming languages
2. Software and its engineering
  1. Software creation and management
    1. Software verification and validation
      1. Process validation
        Traceability
  2. Software notations and tools
    1. General programming languages
      1. Language types
        Parallel programming languages

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Graphical abstract

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- This review reconsiders the anomaly and gives criteria and challenges for anomaly detection.
Abstract
Supervised learning algorithms have shown limited use in the field of anomaly detection due to the unpredictability and difficulty in acquiring abnormal samples. In recent years, unsupervised or semi-supervised anomaly-detection ...

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Published: 01 April 1991

Published in SIGOPS Volume 25, Issue Special Issue

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Armaly AMcMillan C(2016)Pragmatic source code reuse via execution record and replayJournal of Software: Evolution and Process10.1002/smr.179028:8(642-664)Online publication date: 10-May-2016
https://doi.org/10.1002/smr.1790
Kidd NReps TDolby JVaziri M(2011)Finding concurrency-related bugs using random isolationInternational Journal on Software Tools for Technology Transfer10.1007/s10009-011-0197-713:6(495-518)Online publication date: 23-Apr-2011
https://doi.org/10.1007/s10009-011-0197-7
Jun YMcDowell C(2000)Scalable Monitoring Technique for Detecting Races in Parallel ProgramsParallel and Distributed Processing10.1007/3-540-45591-4_44(340-347)Online publication date: 25-May-2000
https://doi.org/10.1007/3-540-45591-4_44
Zhang MWu YLu SQi SRen JZheng W(2016)A Lightweight System for Detecting and Tolerating Concurrency BugsIEEE Transactions on Software Engineering10.1109/TSE.2016.253166642:10(899-917)Online publication date: 1-Oct-2016
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Segulja CAbdelrahman T(2015)CleanACM SIGARCH Computer Architecture News10.1145/2872887.275039543:3S(401-413)Online publication date: 13-Jun-2015
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Kasikci BZamfir CCandea G(2015)Automated Classification of Data Races Under Both Strong and Weak Memory ModelsACM Transactions on Programming Languages and Systems10.1145/273411837:3(1-44)Online publication date: 22-May-2015
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Klein GAndronick JElphinstone KMurray TSewell TKolanski RHeiser G(2014)Comprehensive formal verification of an OS microkernelACM Transactions on Computer Systems10.1145/256053732:1(1-70)Online publication date: 26-Feb-2014
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Qi SMuzahid AAhn WTorrellas J(2014)Dynamically detecting and tolerating IF-Condition Data Races2014 IEEE 20th International Symposium on High Performance Computer Architecture (HPCA)10.1109/HPCA.2014.6835923(120-131)Online publication date: Feb-2014
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