NDLI: Automated Analysis of Multi-Source Logs for Network Forensics

Content Provider	IEEE Xplore Digital Library
Author	Chen Lin Li Zhitang Gao Cuixia
Copyright Year	2009
Abstract	Nowadays, one of the reasons for the lack of legal sanctions taken against attackers is that the collection and analysis of forensic evidence is very troublesome and time-consuming. There are many research results about events correlation but not directly suitable for network forensics. The work presented in this paper is based on an idea to collect the evidences from multiple network sensors and analyze them to improve the quality of forensic evidence automatically. This paper discusses the issues of log evidence first. The framework of IEAAS (Automated Analysis System of Intrusion Evidences) is illustrated with LCA (Log Collection Agent) in network sensors and multiple modules in IEAAS. Analysis mechanism is discussed, particularly the improved aggregation algorithm and evidence preservation method are described. Then a series of experiments are performed to validate our method on actual attack network environments of CERNET. The results of experiments show that our approach is practical and effective for dynamic forensics to augment the computer crime investigators’ efforts.
Starting Page	660
Ending Page	664
File Size	531338
Page Count	5
File Format	PDF
ISBN	9781424435814
DOI	10.1109/ETCS.2009.153
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-03-07
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Law multi-source Digital forensics Educational technology Sensor systems aggregation Computer crime evidence preservation Computer science correlation Intrusion detection dynamic forensics Computer science education Legal factors
Content Type	Text
Resource Type	Article

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