Open Access

ARTICLE

Randomized MILP framework for Securing Virtual Machines from Malware Attacks

by R. Mangalagowri^1,*, Revathi Venkataraman²

1 Computer Science Department, SRM Institute of Science and Technology, Kattankulathur, Tamil Nadu, 603203, India
2 School of Computing, SRM Institute of Science and Technology, Kattankulathur, Tamil Nadu, 603203, India

* Corresponding Author: R. Mangalagowri. Email:

Intelligent Automation & Soft Computing 2023, 35(2), 1565-1580. https://doi.org/10.32604/iasc.2023.026360

Received 23 December 2021; Accepted 23 February 2022; Issue published 19 July 2022

Abstract

Cloud computing involves remote server deployments with public network infrastructures that allow clients to access computational resources. Virtual Machines (VMs) are supplied on requests and launched without interactions from service providers. Intruders can target these servers and establish malicious connections on VMs for carrying out attacks on other clustered VMs. The existing system has issues with execution time and false-positive rates. Hence, the overall system performance is degraded considerably. The proposed approach is designed to eliminate Cross-VM side attacks and VM escape and hide the server’s position so that the opponent cannot track the target server beyond a certain point. Every request is passed from source to destination via one broadcast domain to confuse the opponent and avoid them from tracking the server’s position. Allocation of SECURITY Resources accepts a safety game in a simple format as input and finds the best coverage vector for the opponent using a Stackelberg Equilibrium (SSE) technique. A Mixed Integer Linear Programming (MILP) framework is used in the algorithm. The VM challenge is reduced by a firewall-based controlling mechanism combining behavior-based detection and signature-based virus detection. The proposed method is focused on detecting malware attacks effectively and providing better security for the VMs. Finally, the experimental results indicate that the proposed security method is efficient. It consumes minimum execution time, better false positive rate, accuracy, and memory usage than the conventional approach.

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Keywords

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