JOURNAL ARTICLE

Toward deceiving the intrusion attacks in containerized cloud environment using virtual private cloud‐based moving target defense.

  • Published In: Concurrency & Computation: Practice & Experience, 2023, v. 35, n. 5. P. 1 1 of 3

  • Database: Applied Science & Technology Source Ultimate 2 of 3

  • Authored By: Hyder, Muhammad Faraz; Ahmed, Waqas; Ahmed, Maaz 3 of 3

Abstract

Summary: The container‐based cloud has its distinct security challenges. In this article, moving target defense (MTD) is used to increase the cost and effort of the attacker to exploit resources and follow an attack path to compromise the critical resources in a container‐based cloud. The existing MTD mechanisms for cloud have not focused on intruder prevention inside containerized environment. The proposed solution is one of its kind that utilizes resource movement inside and across the virtual private network in the cloud to deceive intruders. The framework continuously changes the target/container to increase confusion about the routing path, so attackers cannot follow the simple attack path. This obscure cloud architecture increases the delay in attack and gives system/network administrators significant time to use Intrusion Detection mechanisms for countering the attack. The proposed scheme is implemented on the Google Cloud Platform (GCP) by using an extensive network of nodes hosting the stateful pods that are created and destroyed periodically. The experimental analysis confirmed that the proposed scheme substantially increased the attack path length and added obscurity at a low computation cost. However, as per experiments, implementing the proposed scheme in GCP slightly increases the dollar cost. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Concurrency & Computation: Practice & Experience. 2023/02, Vol. 35, Issue 5, p1
  • Document Type:Article
  • Subject Area:Computer Science
  • Publication Date:2023
  • ISSN:15320626
  • DOI:10.1002/cpe.7549
  • Accession Number:161394961
  • Copyright Statement:Copyright of Concurrency & Computation: Practice & Experience is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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