Research On Cache Strategy And Prefetch Model Based On CP-ABE Encrypted Data

With the rapid development of Internet technology,more and more people access and transmit data through the network.In the complex network environment,the importance of data security has received more and more attention.Using encryption technology is an important way to ensure data security.The most commonly used encryption algorithm is CP-ABE.As the amount of ciphertext data in the network increases,the access speed of ciphertext data needs to be further improved.Using the technology of caching and data prefetching can improve the speed of data accessing effectively.However,the methods of caching and data prefetching proposed for plaintext data have some limitations for ciphertext data.Therefore,this thesis studies the caching strategy and prefetching model for CP-ABE encrypted data.This thesis studies the caching problem of CP-ABE encrypted data.According to the attributes of CP-ABE encrypted data,this thesis proposes a new cache replacement algorithm,it is minimal attribute-weight similarity algorithm.The algorithm considers the size of cache data,access time and access frequency.It calculates the attribute similarity of encrypted data by using Pearson correlation coefficient.And it replaces the data with the smallest attribute similarity in the cache.In the research of prefetching technology,this thesis proposes a Markov prefetching model based on attribute classification.It changes the method of classifying users in the Markov prefetching model based on user classification,and applies the modularity-based community partitioning algorithm to classify users.At the end,this thesis builds a caching and prefetching integration model for CP-ABE encrypted data by combining the proposed cache replacement algorithm and prefetching model.This thesis do experiments for the proposed cache strategy,prefetching model,caching and prefetching integration model.Experiments show that the cache replacement algorithm proposed in this thesis has higher cache hit ratio and higher byte hit ratio compared with FIFO algorithm,LRU algorithm,LFU algorithm and SIZE algorithm.The prefetching model proposed in this thesis has higher prefetching accuracy than the traditional Markov prefetching model and the Markov prefetching model based on user classification.The caching and prefetching integration model proposed in this thesis can optimize the performance of the cache and improve the cache hit rate and the byte hit rate of encrypted data.