Efficiency of Network Event logs as Admissible Digital Evidence

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Title: Efficiency of Network Event logs as Admissible Digital Evidence
Authors: Al-Mahrouqi, Aadil
Abdalla, Sameh
Kechadi, Tahar
Permanent link: http://hdl.handle.net/10197/6481
Date: 30-Jul-2015
Abstract: The large number of event logs generated in atypical network is increasingly becoming an obstacle for forensicinvestigators to analyze and use to detect and verify maliciousactivities. Research in the area of network forensics is trying toaddress the challenge of using network logs to reconstruct attackscenarios by proposing events correlation models. In this paperwe introduce and examine a new network forensics model thatmakes network event-logs admissible in the court of low. The ideaof our model is to collect available logs from connected networkdevices and then apply Support Vectors Machine (SVMs) in orderto filter out anomaly intrusion, and re-route these logs to a centralrepository where a event-logs management functions are applied.
Funding Details: Science Foundation Ireland
Type of material: Conference Publication
Start page: 1257
End page: 1265
Copyright (published version): 2015 IEEE
Keywords: Machine learningStatisticsSVMsEvidence reliabilityNetwork evidence admissibilityAuthentication of evidenceBest evidence
DOI: 10.1109/SAI.2015.7237305
Other versions: http://thesai.org/SAIConference2015
Language: en
Status of Item: Peer reviewed
Conference Details: 2015 Science and Information Conference, London, United Kingdom, 28-30 July 2015
Appears in Collections:Computer Science Research Collection
Insight Research Collection

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