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Towards a scalable intrusion detection system based on parallel PSO clustering using mapreduce

Published: 06 July 2013 Publication History

Abstract

The growing data traffic in large networks faces new challenges requiring efficient intrusion detection systems. The analysis of this high volume of data traffic to discover attacks has to be done very quickly. However, in order to be able to process large data, new distributed and parallel methods need to be developed. Several approaches are proposed to build intrusion systems using clustering approaches. In this paper, we introduce an intrusion detection system based on a parallel particle swarm optimization clustering algorithm using the MapReduce framework. The proposed system is scalable in processing large data on commodity hardware.

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J. Dean and S. Ghemawat. Mapreduce: Simplified data processing on large clusters. In Proceedings of the OSDI '04, pages 137--150, 2004.
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J. Kennedy and R. Eberhart. Particle swarm optimization. In Proceedings of the 1995 IEEE International Conference on Neural Networks, pages 1942--1948. Brisbane, Australia, 1995.
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I. Aljarah and S. A. Ludwig. Parallel particle swarm optimization clustering algorithm based on mapreduce methodology. In Proceedings of NaBIC'12, pages 104--111, Mexico, November 2012.
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S. D. Bay, D. Kibler, M. J. Pazzani, and P. Smyth. The uci kdd archive of large data sets for data mining research and experimentation. SIGKDD Explor. Newsl., 2:81--85, December 2000.
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W. Zhu, N. Zeng, and N. Wang. Sensitivity, specificity, accuracy associated confidence interval and roc analysis with practical sas implementations. In In Proceedings NESUG'10 Conference, 2010.

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  • (2022)25 Years of Particle Swarm Optimization: Flourishing Voyage of Two DecadesArchives of Computational Methods in Engineering10.1007/s11831-022-09849-x30:3(1663-1725)Online publication date: 3-Dec-2022
  • (2021)Parallel Particle Swarm Optimization Based on Spark for Academic Paper Co-Authorship PredictionInformation10.3390/info1212053012:12(530)Online publication date: 20-Dec-2021
  • (2021)A Comprehensive Survey on Big Data Technology Based Cybersecurity Analytics SystemsApplied Soft Computing and Communication Networks10.1007/978-981-33-6173-7_9(123-143)Online publication date: 2-Jul-2021
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Published In

cover image ACM Conferences
GECCO '13 Companion: Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
July 2013
1798 pages
ISBN:9781450319645
DOI:10.1145/2464576
  • Editor:
  • Christian Blum,
  • General Chair:
  • Enrique Alba
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 06 July 2013

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Author Tags

  1. data clustering
  2. intrusion detection
  3. mapreduce
  4. parallel processing
  5. particle swarm optimization

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GECCO '13
Sponsor:
GECCO '13: Genetic and Evolutionary Computation Conference
July 6 - 10, 2013
Amsterdam, The Netherlands

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Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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Cited By

View all
  • (2022)25 Years of Particle Swarm Optimization: Flourishing Voyage of Two DecadesArchives of Computational Methods in Engineering10.1007/s11831-022-09849-x30:3(1663-1725)Online publication date: 3-Dec-2022
  • (2021)Parallel Particle Swarm Optimization Based on Spark for Academic Paper Co-Authorship PredictionInformation10.3390/info1212053012:12(530)Online publication date: 20-Dec-2021
  • (2021)A Comprehensive Survey on Big Data Technology Based Cybersecurity Analytics SystemsApplied Soft Computing and Communication Networks10.1007/978-981-33-6173-7_9(123-143)Online publication date: 2-Jul-2021
  • (2021)A Comprehensive Review of Evaluation and Fitness Measures for Evolutionary Data ClusteringEvolutionary Data Clustering: Algorithms and Applications10.1007/978-981-33-4191-3_2(23-71)Online publication date: 21-Feb-2021
  • (2019)Cooperative Asynchronous Parallel Particle Swarm Optimization for Large Dimensional ProblemsInternational Journal of Applied Metaheuristic Computing10.4018/IJAMC.201907010210:3(19-38)Online publication date: Jul-2019
  • (2019)Evolving neural networks using bird swarm algorithm for data classification and regression applicationsCluster Computing10.1007/s10586-019-02913-5Online publication date: 15-Feb-2019
  • (2019)Clustering analysis using a novel locality-informed grey wolf-inspired clustering approachKnowledge and Information Systems10.1007/s10115-019-01358-xOnline publication date: 2-Apr-2019
  • (2019)Multi-objective Particle Swarm Optimization: Theory, Literature Review, and Application in Feature Selection for Medical DiagnosisEvolutionary Machine Learning Techniques10.1007/978-981-32-9990-0_9(175-201)Online publication date: 12-Nov-2019
  • (2019)Multi-objective Particle Swarm Optimization for Botnet Detection in Internet of ThingsEvolutionary Machine Learning Techniques10.1007/978-981-32-9990-0_10(203-229)Online publication date: 12-Nov-2019
  • (2019)Multi-verse Optimizer: Theory, Literature Review, and Application in Data Clustering10.1007/978-3-030-12127-3_8(123-141)Online publication date: 2-Feb-2019
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