Malware Injection Attacks in Resource Virtualization of Cloud Computing Environment

Authors

  • Mansoor Ahmad Rasheed University of Management and Technology

DOI:

https://doi.org/10.21015/vtse.v9i2.830

Abstract

Cloud computing is a procedure which gives us a large, reliable and scalable infrastructure and service. Cloud computing have some features of distributed system, according to these features cloud computing also uses the features of networking. In this technique, there is large number of data sets on the internet. These data sets can be stored and accessed by a remote server. Some common and basic examples of cloud computing are Amazon, Google’s application etc. This technique provides the user to build an online application and to access that from any remote server hosted on internet. We know cloud computing system usually operate on an open network (public) so there comes security issues. The critical part of cloud computing technology is Virtualization. Virtualization refers to creating new system on the machine that is not actual but acts and performs like the actual ones. Cloud Computing and Virtualization give different services by working together. -This paper describes the malware injection attack on virtual systems working in cloud computing environment and their solutions as well. Cloud computing based on sharing technique therefore, the security is the leading crisis of this system. In this paper we discussed the diverse types of malware injection attacks and their possible solutions. Virtual machine emulators have turn out to be conventional in the examination of malicious code. This paper presents notorious attacks for the most extensively used virtual machine emulators. This paper also demonstrates newly exposed attacks on Bochs, Hydra, QEMU, and Xen (other virtual machine emulators), and describes how to protect from them.

 

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Published

2021-07-01

How to Cite

Rasheed, M. A. (2021). Malware Injection Attacks in Resource Virtualization of Cloud Computing Environment. VFAST Transactions on Software Engineering, 9(2), 44–49. https://doi.org/10.21015/vtse.v9i2.830

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