Clustering of optimized data for email forensics
RAIRO - Operations Research - Recherche Opérationnelle, Tome 50 (2016) no. 4-5, pp. 951-963.

Forensics is a study of evidence to help the police solving crimes. If we apply (Forensics) in Computer Sciences domain, crimes are mainly network attacks found more in emails; which become nowadays the most popular way of communication accessible via Internet. We receive in our Inboxes emails gangs without being aware of them. Therefore, it is necessary to build an automatic checking system to filter good emails from bad ones. In this paper, we propose a new emails processing approach using Singular Value Decomposition method (SVD) to optimize emails data before applying Data Mining techniques (Clustering) to extract bad emails located in the mail servers where the user’s inboxes are hosted. Our study is based on filtering Emails (bads and goods) by the clustering of optimized data compared with unoptimized one.

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Accepté le :
DOI : 10.1051/ro/2015057
Classification : 05C12, 05C50, 05B10, 91C20, 15A18, 34A05
Mots clés : Email, feronsics, spam, SVD, LSI, optimisation, data mining, clustering
Salhi, Dhai Eddine 1 ; Tari, Abdelkamel 1 ; Kechadi, M-Tahar 2

1 University Abderrahmane Mira of bejaia, LIMED Laboratory, 06000 Bejaia, Algeria.
2 University college Dublin, Parallel Comptaional Research Group Laboratory, Dublin4, Dublin, Ireland.
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Salhi, Dhai Eddine; Tari, Abdelkamel; Kechadi,  M-Tahar. Clustering of optimized data for email forensics. RAIRO - Operations Research - Recherche Opérationnelle, Tome 50 (2016) no. 4-5, pp. 951-963. doi : 10.1051/ro/2015057. http://www.numdam.org/articles/10.1051/ro/2015057/

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