Secure and Compressed Key-Value Store for Outsourced Data in Cloud Computing

Key-value (KV for short) store is one of the most popular types of data storage for big data in the cloud. For the concern of data security and privacy, many organizations encrypt their data and outsource the data to the cloud. As the data size ever increasing, it is also important to compress the data stored in the cloud. However, it is a challenging task to combine data encryption with compression. The principal goal of this project is to develop an efficient and secure scheme to compress and encrypt the KV stores outsourced to the cloud. There are three tasks of this project: 1) Develop a mathematical model for analysis of storage cost and bandwidth cost in a KV store with data compression and encryption, and determine the optimal pack size for compression to achieve the best trade-off between storage and bandwidth costs. 2) Design an encrypted and compressed KV store that achieves frequency-security and length-security efficiently. The system shall be secure that it hides access frequencies and lengths of KV pairs and shall be efficient that it incurs minimal bandwidth and storage overheads to achieve the specified security requirements. 3) Design the algorithms for the dynamic management of the KV system. It includes the support of insert/delete operations of KV pairs and the dynamic adaptation of the proposed security scheme under the change of access frequencies of KV pairs.