A Lightweight and Fine-Grained Ciphertext Search Scheme for Big Data Assisted by Proxy Servers

In Big Data scenarios, the data volume is enormous. Data computation and storage in distributed manner with more efficient algorithms is promising. However, most current ciphertext search schemes are designed for the centralized cloud computing platforms and they are inefficient and inapplicable in Big Data scenarios. A proxy server based system is a cloud computing extension. This new pattern moves some of the data storage and computation burden from end users to the edge servers and it greatly decrease the resource costs of data users. In this paper, we propose a searchable encryption scheme assisted by cloud computing and proxy servers for Big Data, which can accomplish Lightweight Fine-grained access control and Efficient multi-keyword top-k ciphertext Search synchronously (LFES). To cope with all types of data, we design an innovative fine-grained access control mechanism based on attribute-based encryption and key distribution protocol. Thus, the scheme only allows users with licensed attributes to access data efficiently. Then, a public key searchable encryption scheme is proposed based on privacy Protection Set Intersection (PSI) and the proxy server model. Our scheme greatly reduces the computation burden on end-users and improves retrieval efficiency. Meanwhile, to prevent tampering with stored ciphertexts, a practical data integrity audit mechanism is also designed. Security analysis illustrates that the LFES can resist Chosen Keyword Attack (CKA) and Keyword Guessing Attack (KGA). Finally, the simulation shows that the LFES is efficient and feasible in practice.