Improving the Efficiency of Big Forensic Data Analysis Using NoSQL

被引：0

作者：

Al Sadi, Md Baitul ^{[1
]}

Wimmer, Hayden ^{[1
]}

Chen, Lei ^{[1
]}

Wang, Kai ^{[2
]}

机构：

[1] Georgia Southern Univ, Dept Informat Technol, Statesboro, GA 30458 USA

[2] Georgia Southern Univ, Dept Comp Sci, Statesboro, GA 30458 USA

来源：

10TH EAI INTERNATIONAL CONFERENCE ON MOBILE MULTIMEDIA COMMUNICATIONS (MOBIMEDIA 2017) | 2017年

关键词：

Digital Forensic (DF); NoSQL; Big Data; Big Data Forensic; MongoDB; Document-oriented Database; Autopsy; Internet of Things (IoT);

D O I：

暂无

中图分类号：

TN [电子技术、通信技术];

学科分类号：

0809 ;

摘要：

The rapid growth of Internet of Things (IoT) makes the task for digital forensic more difficult. At the same time, the data analyzing technology is also developing in a feasible pace. Where traditional Structured Query Language (SQL) is not adequate to analyze the data in an unstructured and semi-structured format, Not only Standard Query Language (NoSQL) unfastens the access to analyzing the data of all format. The large volume of data of to I's turns into Big Data which just do not enhance the probability of attaining of evidence of an incident but make the investigation process more complex. This paper aims to analyze Big Data for Digital Forensic (DF) investigation using NoSQL. MongoDB has been used to analyze Big Forensic Data in the form of document-oriented database. The proposed solution is capable of analyzing Big Forensic Data in the form of NoSQL more specifically document oriented data in a cost-effective, efficient way as all the tools is being used are open source.

引用

页码：240 / 248

页数：9

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