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DOI: 10.14569/IJACSA.2021.0120531
PDF

Improving Performance of ABAC Security Policies Validation using a Novel Clustering Approach

Author 1: K. Vijayalakshmi
Author 2: V.Jayalakshmi

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 12 Issue 5, 2021.

  • Abstract and Keywords
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Abstract: Cloud computing offers several services, such as storage, software, networking, and other computing services. Cloud storage is a boon for big data and big data owners. Although big data owners can easily avail cloud storage without spending much on infrastructure and software to manage their data, security is a big issue, and protecting the outsourced big data is challenging and ongoing research. Cloud service providers use the attribute-based access control model to detect malicious intruders and address the security requirements of today’s new computing technologies. Anomalies in security policies are removed to improve the efficiency of the access control model. This paper implements a novel clustering approach to cluster security policies. Our proposed approach uses a rule-specific cluster merging technique that compares the rule with the clusters where the probability of similarity is high. Hence this technique reduces the cost, time, and complexity of clustering. Rather than verifying all rules, detecting and removing anomalies in every cluster of rules improve the performance of the intrusion detection system. Our novel clustering approach is useful for the researchers and practitioners in the ABAC policy validation.

Keywords: Anomalies; attribute-based access control model; big data; cloud storage; clustering; intrusion detection system; security policy

K. Vijayalakshmi and V.Jayalakshmi, “Improving Performance of ABAC Security Policies Validation using a Novel Clustering Approach” International Journal of Advanced Computer Science and Applications(IJACSA), 12(5), 2021. http://dx.doi.org/10.14569/IJACSA.2021.0120531

@article{Vijayalakshmi2021,
title = {Improving Performance of ABAC Security Policies Validation using a Novel Clustering Approach},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2021.0120531},
url = {http://dx.doi.org/10.14569/IJACSA.2021.0120531},
year = {2021},
publisher = {The Science and Information Organization},
volume = {12},
number = {5},
author = {K. Vijayalakshmi and V.Jayalakshmi}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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