Classifying malicious thread behavior in paas web services

Cemile Diler Özdemir*, Mehmet Tahir Sandikkaya, Yusuf Yaslan

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)

Abstract

Multitenant structure of PaaS cloud delivery model allows customers to share the platform resources in the cloud. However, this structure requires a strong security mechanism that isolates customer applications to prevent interference between different applications. In this paper, a malicious thread behavior detection framework using machine learning algorithms is proposed to classify whether user requests are malicious. The framework uses thread metrics of worker threads and N-Gram frequencies of operations as its features. Test results are evaluated on a real-life scenario using Random Forest, Adaboost and Bagging ensemble learning algorithms and evaluated using different accuracy metrics. It is found that the malicious request detection accuracy of the proposed system is 87.6%.

Original languageEnglish
Title of host publicationCLOSER 2018 - Proceedings of the 8th International Conference on Cloud Computing and Services Science
EditorsVictor Mendez Munoz, Donald Ferguson, Markus Helfert, Claus Pahl
PublisherSciTePress
Pages418-425
Number of pages8
ISBN (Electronic)9789897582950
DOIs
Publication statusPublished - 2018
Event8th International Conference on Cloud Computing and Services Science, CLOSER 2018 - Funchal, Madeira, Portugal
Duration: 19 Mar 201821 Mar 2018

Publication series

NameCLOSER 2018 - Proceedings of the 8th International Conference on Cloud Computing and Services Science
Volume2018-January

Conference

Conference8th International Conference on Cloud Computing and Services Science, CLOSER 2018
Country/TerritoryPortugal
CityFunchal, Madeira
Period19/03/1821/03/18

Bibliographical note

Publisher Copyright:
Copyright © 2018 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved.

Keywords

  • Cloud security
  • Machine learning
  • Malicious behavior
  • PaaS

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