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Forensic Analysis of Residual Artifacts on CDH Storage
http://hdl.handle.net/20.500.12678/0000006259
http://hdl.handle.net/20.500.12678/00000062597660e6e6-69b2-4c6d-9f66-3ec31b50bd0b
a0fc1a36-bee5-43e8-9076-4c98078f283e
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© 2017 ICAIT
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| Publication type | ||||||
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| Conference paper | ||||||
| Upload type | ||||||
| Publication | ||||||
| Title | ||||||
| Title | Forensic Analysis of Residual Artifacts on CDH Storage | |||||
| Language | en | |||||
| Publication date | 2017-11-02 | |||||
| Authors | ||||||
| Myat Nandar Oo | ||||||
| Thandar Thein | ||||||
| Description | ||||||
| Hadoop Storage is increasingly used by consumers, business, and government, and can potentially store and process large amounts of data. With the maturing and wide usage of Hadoop Storage, there are more and more crimes in this environment. The retrieval of digital evidence from Hadoop Storage can be a challenge in forensic investigation, due to its complex infrastructure and, lack of location knowledge about digital evidences. As a consequence, forensic researchers are moving towards the investigation researches of locating and documenting the residual artifacts to trace the criminal activities of Hadoop Storage. The Cloudera Distribution Hadoop (CDH) is a popular Hadoop Storage Platform, providing users a cost-effective, and in some cases free with the ability to access, store, and process data. This paper proposes a forensic investigation framework for locating and discovering the residual artifacts that remain on the CDH Storage Server and attached client machine. The residual artifacts can provide the potential evidences for forensic examiners to extract the evidences, and reconstruct the crime scene. | ||||||
| Keywords | ||||||
| CDH, crime, forensics investigation framework, residual artifacts | ||||||
| Conference papers | ||||||
| ICAIT-2017 | ||||||
| 1-2 November, 2017 | ||||||
| 1st International Conference on Advanced Information Technologies | ||||||
| Yangon Myanmar | ||||||
| Cloud Computing and Big Data Analytics | ||||||
| https://www.uit.edu.mm/icait-2017/ | ||||||