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

—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.