Prevention of VM Timing side-channel attack in a cloud environment using randomized timing approach in AES – 128

  • Animesh Kumar Department of Computer Science and Engineering, Birla Institute of Technology, Mesra, Ranchi, Jharkhand, India https://orcid.org/0009-0007-3679-8025
  • Sandip Dutta Department of Computer Science and Engineering, Birla Institute of Technology, Mesra, Ranchi, Jharkhand, India https://orcid.org/0000-0002-3932-3048
  • Prashant Pranav Department of Computer Science and Engineering, Birla Institute of Technology, Mesra, Ranchi, Jharkhand, India https://orcid.org/0000-0002-3932-3048
Keywords: Cloud computing, Security, Cryptography, VM side-channel attack, Side channel attack, Virtual Machine (VM)

Abstract

The term "cloud computing" refers to the delivery of various computer services to users via the Internet. These services include servers, storage, databases, networking, software, and analytics. The ability for businesses to swiftly and easily access computing resources as needed is one of the primary benefits of cloud computing, along with scalability, flexibility, and cost savings. To protect themselves from data breaches, distributed denial of service attacks, and insider threats, cloud providers and consumers alike need to deploy adequate security measures. Shared resources and timing inconsistencies within the hypervisor can make it possible for attackers to deduce sensitive information from other Virtual Machines (VMs). In this research, a software-based solution to the problem of VM timing side-channel assaults (SCAs) in CC (Cloud Computing) is proposed. Following an analysis of the process's empirical complexity, the solution uses a randomized timing method, which is compatible with all of the AES–128 sub-steps.

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Published
2023-07-30
How to Cite
Kumar, A., Dutta, S., & Pranav, P. (2023). Prevention of VM Timing side-channel attack in a cloud environment using randomized timing approach in AES – 128. International Journal of Experimental Research and Review, 31(Spl Volume), 131-140. https://doi.org/10.52756/10.52756/ijerr.2023.v31spl.013