Secure Remote Cloud File Sharing With Attribute-Based Access Control and Performance Optimization

The increasing popularity of remote Cloud File Sharing (CFS) has become a major concern for privacy breach sensitive data. Aiming at this concern, we present new resource sharing framework by integrating enterprise-side Attribute-Based Access Control/eXtensible Control Markup Language (ABAC/XACML) model, client-side Ciphertext-Policy Encryption (CP-ABE) scheme, and cloud-side CFS service. Moreover, the workflow is provided to support encrypted-file writing reading algorithms in accordance with ABAC/XACML-based access policy attribute credentials. However, an actual problem realizing that matrix, derived from policy, seriously affects performance existing CP-ABE Lattice (CP-ABE-L) schemes. To end it, optimal generation algorithm Small Policy Matrix (SPM), which only consists small elements, generates all-one reconstruction vector. Based on such improved CP-ABE-L scheme proposed reduce cumulative errors minimum prevent enlargement error bounds. Furthermore, give estimation system parameters implement valid Error Proportion Allocation (EPA). Our experimental results indicate our short size enjoys efficient computation storage overloads. Thus, optimization methods conducive enhancing security efficiency work CFS.