This research proposes a neural-based fuzzy framework-based approach for estimating reusable components that are directly or indirectly involved in security and privacy in order to improve the software system’s quality. This method took into account twenty influencing elements and fifty-three attribute matrices. It has three stages of execution possibilities in place. The first stage used eleven effecting factors and eighteen attribute matrices to identify supporting software reusability components, the second stage used four effecting factors and 35 attribute matrices to identify sub-internal relationships in terms of security and privacy, and the third stage used eight effecting factors and six attribute matrices to identify sub-internal relationships in terms of security and privacy. In the component-based software reusability development process, software engineers must select the best components that are self-adaptive in the future to avoid functional faults, framework mismatches, privacy violations at the user level, and data leakage risks. Software developers can create high-quality software applications by considering reusable components that are more suited to providing high levels of data security and privacy. This research provides a fuzzy logic model to assess the most likely influencing elements on enterprise data security and privacy policies in a real-time setting.
T. Rajani Devi
Department of Computer Science, Kakatiya University, India
Department of Computer Science, Kakatiya University, India.
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