Open Access

ARTICLE

Real-Time Multi Fractal Trust Evaluation Model for Efficient Intrusion Detection in Cloud

S. Priya¹, R. S. Ponmagal^2,*

1 Department of Computer Science and Engineering, School of Computing, SRM Institute of Science and Technology, Chengapattu, 603 203, Tamil Nadu, India
2 Department of Computing Technologies, School of Computing, SRM Institute of Science and Technology, Chengapattu, 603 203, Tamil Nadu, India

* Corresponding Author: R. S. Ponmagal. Email:

Intelligent Automation & Soft Computing 2023, 37(2), 1895-1907. https://doi.org/10.32604/iasc.2023.039814

Received 18 February 2023; Accepted 14 April 2023; Issue published 21 June 2023

Abstract

Handling service access in a cloud environment has been identified as a critical challenge in the modern internet world due to the increased rate of intrusion attacks. To address such threats towards cloud services, numerous techniques exist that mitigate the service threats according to different metrics. The rule-based approaches are unsuitable for new threats, whereas trust-based systems estimate trust value based on behavior, flow, and other features. However, the methods suffer from mitigating intrusion attacks at a higher rate. This article presents a novel Multi Fractal Trust Evaluation Model (MFTEM) to overcome these deficiencies. The method involves analyzing service growth, network growth, and quality of service growth. The process estimates the user’s trust in various ways and the support of the user in achieving higher service performance by calculating Trusted Service Support (TSS). Also, the user’s trust in supporting network stream by computing Trusted Network Support (TNS). Similarly, the user’s trust in achieving higher throughput is analyzed by computing Trusted QoS Support (TQS). Using all these measures, the method adds the Trust User Score (TUS) value to decide on the clearance of user requests. The proposed MFTEM model improves intrusion detection accuracy with higher performance.

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Keywords

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