Role of Bloom Filter in Big Data Research: A Survey

Abstract

Big Data is the most popular emerging trends that becomes a blessing for human kinds and it is the necessity of day-to-day life. For example, Facebook. Every person involves with producing data either directly or indirectly. Thus, Big Data is a high volume of data with exponential growth rate that consists of a variety of data. Big Data touches all fields, including Government sector, IT industry, Business, Economy, Engineering, Bioinformatics, and other basic sciences. Thus, Big Data forms a data silo. Most of the data are duplicates and unstructured.To deal with such kind of data silo, Bloom Filter is a precious resource to filter out the duplicate data. Also, Bloom Filter is inevitable in a Big Data storage system to optimize the memory consumption. Undoubtedly, Bloom Filter uses a tiny amount of memory space to filter a very large data size and it stores information of a large set of data. However, functionality of the Bloom Filter is limited to membership filter, but it can be adapted in various applications. Besides, the Bloom Filter is deployed in diverse field, and also used in the interdisciplinary research area. Bioinformatics, for instance. In this article, we expose the usefulness of Bloom Filter in Big Data research.

SBI Model for the Detection of Advanced Persistent Threat Based on Strange Behavior of Using Credential Dumping Technique

“…The total data gathered from the registry, file system, and CBU are 737 bytes, and the rest of the three Giga was from RAM. The RAM is 1000 times faster read rate compared with hard disk drive HDD [34]. This means it takes 50 x 1000 = 50,000 NS to read one byte from HDD, accordingly, the required time to read 737 bytes is 737 x 50,000 = 36,850,000 NS.…”

“…The detection accuracy scenario evaluates the detection accuracy of the proposed Strange Behavior Inspection Model over the SBI dataset. Based on [32]- [33]- [34] the access period to read or write any specific byte is autonomous of whereabouts in the memory that byte is, and is approximately 50 nanoseconds, and 50,000 ns to read from HDD. The real detection time is described in details in section (terrestrial observations detection accuracy scenario).…”

The Potential of Big Data Research in HealthCare for Medical Doctors’ Learning

“…Nowadays MDs are also being required to support healthcare businesses to learn and quickly distil new information from masses of data [23] and transform them into actionable insights regarding cost reduction, maximisation of treatment options, diagnostic pathways, or new solutions to various problems impacting financial and human resources. The ability to extract these insights will empower the future of health and become a differentiator for companies and organiations to thrive and stay ahead of emerging competitors [24][25][26]. Continuous medical education allows for the improving of MDs' knowledge, preparing healthcare professionals to care for and diagnose in a very demanding and highly technological, multidisciplinary environment [23,27].…”

A Review on Role of Bloom Filter on DNA Assembly

“…Bloom Filter is classified mainly into four key categories [27], namely, standard Bloom Filter, counting Bloom Filter, Hierarchical Bloom Filter, and multidimensional Bloom Filter. Standard Bloom Filter has scalability and deletion issue, and that's why counting Bloom Filter is initiated.…”

“…It found its applications in many domains. Bloom Filter is used in the flash memory to maximize the data storage [27]. Debnath et al [28] proposed a flash memory based storage called BloomFlash.…”