A Design of an Integrated Cloud-based Intrusion Detection System with Third Party Cloud Service

Wisam Elmasry*, Akhan Akbulut, Abdul Halim Zaim

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

28 Citations (Scopus)

Abstract

Although cloud computing is considered the most widespread technology nowadays, it still suffers from many challenges, especially related to its security. Due to the open and distributed nature of the cloud environment, this makes the cloud itself vulnerable to various attacks. In this paper, the design of a novel integrated Cloud-based Intrusion Detection System (CIDS) is proposed to immunise the cloud against any possible attacks. The proposed CIDS consists of five main modules to do the following actions: monitoring the network, capturing the traffic flows, extracting features, analyzing the flows, detecting intrusions, taking a reaction, and logging all activities. Furthermore an enhanced bagging ensemble system of three deep learning models is utilized to predict intrusions effectively. Moreover, a third-party Cloud-based Intrusion Detection System Service (CIDSS) is also exploited to control the proposed CIDS and provide the reporting service. Finally, it has been shown that the proposed approach overcomes all problems associated with attacks on the cloud raised in the literature.

Original languageEnglish
Pages (from-to)365-379
Number of pages15
JournalOpen Computer Science
Volume11
Issue number1
DOIs
Publication statusPublished - 1 Jan 2021
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2021 Wisam Elmasry et al., published by De Gruyter 2021.

Keywords

  • Cloud Security
  • Deep Learning
  • Ensemble System
  • Intrusion Detection
  • Particle Swarm Optimization

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