학술논문

Markov Encrypted Data Prefetching Model Based On Attribute Classification
Document Type
Conference
Source
2020 5th International Conference on Computer and Communication Systems (ICCCS) Computer and Communication Systems (ICCCS), 2020 5th International Conference on. :54-59 May, 2020
Subject
Communication, Networking and Broadcast Technologies
Markov processes
Prefetching
Hidden Markov models
Cryptography
Classification algorithms
Partitioning algorithms
Data models
attribute
markov
data prefetch
CP-ABE
modularity
encrypted
Language
Abstract
In order to improve the buffering performance of the data encrypted by CP-ABE (ciphertext policy attribute based encryption), this paper proposed a Markov prefetching model based on attribute classification. The prefetching model combines the access strategy of CP-ABE encrypted file, establishes the user relationship network according to the attribute value of the user, classifies the user by the modularity-based community partitioning algorithm, and establishes a Markov prefetching model based on attribute classification. In comparison with the traditional Markov prefetching model and the classification-based Markov prefetching model, the attribute-based Markov prefetching model is proposed in this paper has higher prefetch accuracy and coverage.