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DDCFS: A Distributed Dynamic Computer Forensic System Based on Network

Authors: Liang Hu; Kuo Tang; Guangkun Shi; null Nurbol; Kuo Zhao;

DDCFS: A Distributed Dynamic Computer Forensic System Based on Network

Abstract

With the increasing development of information technology, the computer crime problem is getting even serious. However traditional computer forensic that employs the static investigation after security events has inherent limitations. The authenticity, effectiveness and timeliness of the evidence are difficult to meet real needs. In order to solve the existing problems which static forensics technology has, this paper presents the design and implementation of DDCFS: a distributed dynamic computer forensics system based on network. Comparing with the traditional tools of the forensic system, it employs the work of gathering evidences of criminal actions before they occur or just they are ongoing, which avoid the evidence chain lose caused by traditional static forensic. It can improve the efficiency of the work of gathering evidences; enhance data integrity and timeliness of evidences. This paper describes the architecture, function and forensic procedure of DDCFS, and the implementation of the core module.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Average
Average
Average
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