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Forensic Investigation Through Data Remnants on Hadoop Big Data Storage System

Myat Nandar Oo1, Sazia Parvin2, Thandar Thein3

1 University of Computer Studies, Yangon
2 University of New South Wales, Canberra
3 University of Computer Studies, Maubin
E-mail: myatnandaroo@gmail.com, saziap@gmail.com, thandartheinn@gmail.com

Computer Systems Science and Engineering 2018, 33(3), 203-217. https://doi.org/10.32604/csse.2018.33.203

Abstract

Forensic examiners are in an uninterrupted battle with criminals in the use of Big Data technology. The underlying storage system is the main scene to trace the criminal activities. Big Data Storage System is identified as an emerging challenge to digital forensics. Thus, it requires the development of a sound methodology to investigate Big Data Storage System. Since the use of Hadoop as Big Data Storage System continues to grow rapidly, investigation process model for forensic analysis on Hadoop Storage and attached client devices is compulsory. Moreover, forensic analysis on Hadoop Big Data Storage System may take additional time without knowing where the data remnants can reside. In this paper, a new forensic investigation process model for Hadoop Big Data Storage System is proposed and discovered data remnants are presented. By conducting forensic research on Hadoop Big Data Storage System, the resulting data remnants assist the forensics examiners and practitioners for generating the evidences.

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Cite This Article

APA Style
Oo, M.N., Parvin, S., Thein, T. (2018). Forensic investigation through data remnants on hadoop big data storage system. Computer Systems Science and Engineering, 33(3), 203-217. https://doi.org/10.32604/csse.2018.33.203
Vancouver Style
Oo MN, Parvin S, Thein T. Forensic investigation through data remnants on hadoop big data storage system. Comput Syst Sci Eng. 2018;33(3):203-217 https://doi.org/10.32604/csse.2018.33.203
IEEE Style
M.N. Oo, S. Parvin, and T. Thein "Forensic Investigation Through Data Remnants on Hadoop Big Data Storage System," Comput. Syst. Sci. Eng., vol. 33, no. 3, pp. 203-217. 2018. https://doi.org/10.32604/csse.2018.33.203



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