Chapter 16 - Bloom Filter in cloud computing

Abstract

Nowadays, cloud computing is extensively used for data storage and computation by many institutions and businesses. Cloud provides a variety of computational services, such as the latest and most sophisticated software, platform, and infrastructure. The user has to pay for the consumed services. To provision the latest and most sophisticated software, the cloud has to execute optimized, efficient, and high-performance processes. Data owners share their data with other users by saving the data in the cloud. The data owners and users pay to the cloud, and the cloud takes responsibility for data management and security. To increase privacy, data owners store encrypted data instead of plaintext. However, indexing and searching the encrypted data is difficult and time-consuming. Some issues related to data storage and management are data deletion and data deduplication. The data deletion is important to the data users because all rights on the data are with the data owner. However, the implementation of fine-grain deletion is difficult. Similarly, data deduplication is essential to reduce the burden on Big data storage, access, retrieval, and analysis. All these problems are solved by implementing Bloom Filter-based techniques. Bloom Filter, with its simple data structure and fastest operation, enhances the performance of the techniques drastically. This chapter focuses on the role of the Bloom Filter in cloud computing. The chapter also provides reviews of many Bloom Filter-based techniques for cloud computing. A brief discussion is also presented at the end of the chapter. Tables are included to highlight the features and limitations of the reviewed technique. The chapter also includes a comparison between these techniques based on various parameters.