Abstract
Bloom Filter is a probabilistic membership data structure. It is an excessively used data structure for the membership query. Bloom Filter enhances the query response time using a very small amount of memory space to save information of a large dataset. Bloom Filter is used to detect whether an item belongs to a given set or not, and it is a widely adapted data structure in numerous areas to enhance the performance of a system. Bloom Filter becomes the predominant data structure in Computer Networking, Cloud Computing, Big Data, Bioinformatics, Biometrics, and Internet-of-Things. For instance, Bloom Filter is extensively used in Computer Networking, and thus, researchers extensively experiment to enhance the performance of Bloom Filter to boost the performance of computer networks. Therefore, numerous variants of Bloom Filter have been developed. Bloom Filter is used in Network Security, Software-defined Network, Content-centric Network, and Named Data Network. In this chapter, we present in-depth details of the Bloom Filter and its applications in various research domains.
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