An Efficient Distributed Forensic System Based on Hadoop:Principle and Method

Songyang Wu; Xizhe Zhang; Xupeng Wang; Xiangxue Li

doi:10.3969/j.issn.1000-0801.2014.01.005

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An Efficient Distributed Forensic System Based on Hadoop:Principle and Method

Research and development | 更新时间：2024-06-05

- An Efficient Distributed Forensic System Based on Hadoop:Principle and Method
- Telecommunications Science Vol. 30, Issue 1, Pages: 31-38(2014)
- 作者机构：
  
  1. 公安部第三研究所上海201204
  2. 华东师范大学上海200241
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.1000-0801.2014.01.005
  CLC：
- Published Online：2014-01，
  
  Published：20 January 2014
- 稿件说明：
移动端阅览
Songyang Wu, Xizhe Zhang, Xupeng Wang, et al. An Efficient Distributed Forensic System Based on Hadoop:Principle and Method[J]. Telecommunications science, 2014, 30(1): 31-38.
DOI：

Songyang Wu, Xizhe Zhang, Xupeng Wang, et al. An Efficient Distributed Forensic System Based on Hadoop:Principle and Method[J]. Telecommunications science, 2014, 30(1): 31-38. DOI： 10.3969/j.issn.1000-0801.2014.01.005.

摘要

随着信息技术的发展以及各种智能设备的普及，设备的平台多样化使得现有电子数据勘查取证分析装备已不能满足网络和存储技术所需要的高速数据镜像存储和海量数据相关性分析等要求，并表现出操作复杂、效率低等缺陷。设计并实现了一种高效的基于Hadoop的分布式取证系统，它能够支持多介质并行取证的工作场景，并通过调度控制服务将不同的证据介质中的数据存储到不同的分布式数据存储服务器上，每个取证任务运行时都可以独占一个取证介质，从而实现多介质的并行取证分析。实验数据显示，搜索一个2～4GB的文本数据的响应时间可以达到仅0.1s。

Abstract

With the development and popularization of information technology and intelligence device

the diversity of different device making forensic analysis of existing equipment cannot meet today's networking and storage technology requirements

and exhibit complex operation

low efficiency

on high speed disk image storage and massive data correlation. An efficient distributed forensics system based on Hadoop technique

which can support multiple concurrent media scene forensics work

was designed and implemented

and through the dispatch control services would be evidence of different data storage media to a different distributed data storage server

each forensic task runtime could monopolize a forensic medium to achieve a parallel multiple media forensic analysis. Data show that responsible acknowledge duration will be 0.1 s for a 2～4 GB text file.

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references

Wang X Q . How to discover the truth in data . China Information Security , 2009 （ 11 ）: 23 ～ 24

Intel Corporation . Understanding the Flash Translation Layer （FTL）Specification , December 1998

King C , Vidas T . Empirical analysis of solid state disk data retention when used with contemporary operating systems . Digital Investigation , 2011 （ 8 ）: 111 ～ 117

Wikipedia Apache Hadoop . http://en.wikipedia.org/wiki/Hadoop http://en.wikipedia.org/wiki/Hadoop , 2013

Analyzing big data with Hadoop, decorated a new history . http://www.bloter.net/archives/68650 http://www.bloter.net/archives/68650 , 2011

Zhou W C , Tao T , Boon T L , et al . Declarative secure distributed information systems . Computer Languages,Systems and Structures , 2013 , 39 （ 1 ）: 1 ～ 24

Jens D , Jorge-Arnulfo . Efficient big data processing in Hadoop MapReduce . Proceedings of the VLDB Endowment , 2012 , 5 （ 12 ）: 2014 ～ 2015

Prashant S , Kamalakar K . A multi-agent simulation framework on small Hadoop cluster . Engineering Applications of Artificial Intelligence , 2011 , 24 （ 7 ）: 1120 ～ 1127

Wang S G , Su W , Zhu X L , et al . A Hadoop-based approach for efficient web service management . International Journal of Web and Grid Services , 2013 , 9 （ 1 ）: 18 ～ 34

Wu T Y , Chen C Y , Kuo L S , et al . Cloud-based image processing system with priority-based data distribution mechanism , 2012 , 35 （ 15 ）: 1809 ～ 1818

Zhao M , Mao R , Jiang R . Transparent encryption file system model based on filter driver.Computer Engineering , 2009 （ 15 ）: 51

Kathleen E , Shrideep P . On the performance of high dimensional data clustering and classification algorithms . Future Generation Computer Systems , 2013 , 29 （ 4 ）: 1024 ～ 1034

Satish N S , Pelle J , Eero V . Adapting scientific computing problems to clouds using MapReduce . Future Generation Computer Systems , 2012 , 28 （ 10 ）: 184 ～ 192

Jiang D W , Deng C O , Shi L , et a . The performance of MapReduce: an in-depth study . Proceedings of the VLDB Endowment , 2010 , 3 （ 1/2 ）: 472 ～ 483

Erik R . The Odd couple: hardware and software . IEEE Micro , 2012 , 32 （ 4 ）: 2 ～ 2

Neal L . Bringing big analytics to the masses . Computer , 2013 , 46 （ 1 ）: 20 ～ 23

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