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Abstract. The cloud computing phenomenon has achieved global popularity, with enterprises increasingly relying on cloud services for day-to-day business operations. However, the rapid dissemination of new malicious code variants with zero-day assaults in the cloud creates confusion and broad worry because the attackers' motives often remain unknown. This paper discusses a safer computing platform or model that detects harmful or malicious code in a cloud environment and automatically selects the best security control for defence. Automated selection of the best security controls for real-time defence is crucial in cloud environments. The study utilizes pefile library in Python to extract signature bytes, N-gram algorithm for signature bytes segmentation, the C4.5 algorithm for constructing signature clusters, and a Python program to determine the best security control. The model was developed and tested using Microsoft Azure and the Amazon Web Services cloud infrastructure, with results demonstrating its effectiveness on both platforms in detecting malicious code and timely selecting an optimal security control for real-time defence.
Keywords: Cloud services, Security, N-gram, C4.5 algorithm
1. Introduction
Cloud computing is gaining global traction, with more businesses transferring their data and operations from traditional servers to cloud servers. This phenomenon refers to the on-demand distribution of information technology resources, which provides clients with access to a shared pool of computer resources at on-demand or pay-per-use rates (Subramanian & Jeyaraj, 2018)
According to (Asadi et al, 2019) cloud computing provides and facilitates client access to a shared pool of configurable computer resources such as networks, servers, applications, and services. Despite the benefits, security control is still a big challenge in Cloud Computing platforms (Rios et al., 2019) The continual creation of new harmful code offers a significant challenge to robust cybersecurity. Organisations must carefully select appropriate security policies to secure sensitive data and reduce potential threats. The typical procedure of determining appropriate security controls based on system technology, known vulnerabilities, and attack patterns is time-consuming, error-prone, and requires extensive knowledge (An et al, 2019). Traditional techniques for establishing security controls frequently result in considerable compromises in core functional processes and security needs (Ehrlich et al., 2019).
The continuous development of new malicious codes also puts intense pressure on software and anti-virus companies to update their database definitions from time to time, which...