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2nd International Conference on Materials Science and Sustainable Manufacturing Technology

Hybrid Approach of Big Data File Classification Based on Threat Analysis for Enhancing Security

Saranya N, Department of Computer Science and Engineering, Sri Eshwar College of Engineering, Coimbatore, India.
Online First : 07 June 2023
Publisher Name : AnaPub Publications, Kenya.
ISBN (Online) : 978-9914-9946-9-8
ISBN (Print) : 978-9914-9946-8-1
Pages : 155-162

DOI
https://doi.org/10.53759/acims/978-9914-9946-9-8_24
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Abstract

Big Data is rapidly growing domain across various real time areas like Banking, Finance, Indusrty, Medicine, Trading and so on. Due to its diversified application, handling the big data for security during data transmission or management is highly risky. Most of the researchers try to handle big data classification based on the domain of interest for increasing productivity or customer satisfaction in decision making. Whereas, this paper focuses on the classification of big data file to enhance security during the data transmission over network and management.Most of the big data applications contains valuable and confidential data. The existing data security approaches are not sufficient on handling the security for data based on the threat level. Therefore, this paper proposes a hybrid approach to classify the big data based on the threat level of the contents associated with the data under consideration into open and close. To ensure the security of big data files, they are transmitted into the Hadoop Distributed File System along with relevant information to assess the level of threat they pose. The Threat Impact Level (TIL) is then calculated as a metric to determine the threshold level required for their protection.

Keywords

Data Security, Big Data, Hadoop Distributed File System, Classification, Threat Impact Level.

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Cite this article

Saranya N, “Hybrid Approach of Big Data File Classification Based on Threat Analysis for Enhancing Security”, Advances in Computational Intelligence in Materials Science, pp. 155-162, May. 2023. doi:10.53759/acims/978-9914-9946-9-8_24

Copyright

© 2023 Saranya N. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                           

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