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openalexJournal of Intelligent Decision Making and Information Science2026-07-23Cited by 0

Probabilistic Analysis of Attribute-Based Encryption Schemes

Akshata Snehal Patil

Effective management of the access to sensitive information remains an overriding issue for organizations. Attribute-based encryption (ABE) allows a cryptographic solution to limit decryption to users with particular sets of attributes. In this work we formulate access control as a prediction problem on the dataset of Amazon employee access, which consists of 32 769 labelled records and 58 921 test records. Employee attributes such as resource identifiers, departmental positions and job titles constitute the feature set. After the preprocessing of the data and introduction of probabilistic model inspired by ABE, we compare the standard classifiers against our proposed method. The proposed probabilistic ABE analysis model got 97.36% accuracy, 96.98% precision and 96.71% F1-score result, which are superior to traditional logistic regression and tree methods. These outcomes suggest that a probabilistic view toward ABE policies can have a meaningful impact on automated access decisions in a complex organizational environment.

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openalexJournal of Intelligent Decision Making and Information Science2026-07-23

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openalexJournal of Intelligent Decision Making and Information Science2026-07-23

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crossrefJournal of Intelligent Decision Making and Information Science2026-06-30

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openalexJournal of Intelligent Decision Making and Information Science2026-07-23

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openalexJournal of Intelligent Decision Making and Information Science2026-07-23

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