A Binary-based MapReduce Analysis for Cloud Logs
| Autor: | Meryem Amar, Mouad Lemoudden, Bouabid El Ouahidi |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Computer science
Big data 0211 other engineering and technologies Binary number Cloud computing 02 engineering and technology computer.software_genre log management big data 020204 information systems 0202 electrical engineering electronic engineering information engineering cloud Log management General Environmental Science 021110 strategic defence & security studies business.industry predict security attacks Variety (cybernetics) Task (computing) Programming paradigm General Earth and Planetary Sciences Data mining binary approach business logs computer |
| Zdroj: | ANT/SEIT |
| ISSN: | 1877-0509 |
| DOI: | 10.1016/j.procs.2016.04.253 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|