Testing of algorithms for anomaly detection in Big data using apache spark

S. N. Lighari, D. M. A. Hussain

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

12 Citations (Scopus)
Original languageEnglish
Title of host publication2017 9th International Conference on Computational Intelligence and Communication Networks (CICN)
Number of pages4
PublisherIEEE
Publication date1 Sept 2017
Pages97-100
ISBN (Electronic)978-1-5090-5001-7
DOIs
Publication statusPublished - 1 Sept 2017
EventIEEE 9th International Conference on Computational Intelligence and Communication Networks (CICN 2017) - Girne, Cyprus
Duration: 16 Sept 201717 Sept 2017

Conference

ConferenceIEEE 9th International Conference on Computational Intelligence and Communication Networks (CICN 2017)
Country/TerritoryCyprus
CityGirne
Period16/09/201717/09/2017
SeriesInternational Conference on Computational Intelligence and Communication Networks (CICN)
ISSN2472-7555

Keywords

  • Bayes methods
  • Big Data
  • data analysis
  • decision trees
  • learning (artificial intelligence)
  • parallel processing
  • pattern classification
  • pattern clustering
  • regression analysis
  • security of data
  • support vector machines
  • Decision trees
  • Kddcup99 dataset
  • Kmeans
  • Naïve bayes
  • Random forest
  • Support vector machine
  • anomaly detection
  • apache spark
  • big data security analysis
  • big data security analytics
  • big data tool
  • logistic regression
  • machine learning algorithms
  • Classification algorithms
  • Prediction algorithms
  • Predictive models
  • Sparks
  • Tools
  • Training
  • Big data
  • Machine learning
  • Security analytics

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