Mouad Lemoudden M.Lemoudden@napier.ac.uk
Lecturer
Efficiently managing and analyzing cloud logs is a difficult and expensive task due the growth in size and variety of formats. In this paper, we propose a binary-based approach for frequency mining correlated attacks in log data. This approach is conceived to work using the MapReduce programming model. Initial experimental results are presented and they serve as the subject of a data mining algorithm to help us predict the likelihood of correlated attacks taking place.
Lemoudden, M., Amar, M., & El Ouahidi, B. (2016). A Binary-based MapReduce Analysis for Cloud Logs. Procedia Computer Science, 83, 1213-1218. https://doi.org/10.1016/j.procs.2016.04.253
Journal Article Type | Article |
---|---|
Online Publication Date | May 12, 2016 |
Publication Date | 2016 |
Deposit Date | Feb 28, 2023 |
Publicly Available Date | Feb 28, 2023 |
Journal | Procedia Computer Science |
Print ISSN | 1877-0509 |
Publisher | Elsevier |
Peer Reviewed | Peer Reviewed |
Volume | 83 |
Pages | 1213-1218 |
DOI | https://doi.org/10.1016/j.procs.2016.04.253 |
Keywords | cloud, big data, logs, log management, binary approach, predict security attacks |
A Binary-based MapReduce Analysis For Cloud Logs
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