Abstract
We propose a method for botnet detection from darknet data by non-negative matrix factorization (NMF), which can decompose the vector valued time series data into several components. In addition, we propose a new method to estimate the number of components in the data, by the minimum description length (MDL) principle. Our method for botnet detection consists of change point detection and analysis based on variance of the decomposed data. © 2012 Springer-Verlag.
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CITATION STYLE
Yamauchi, S., Kawakita, M., & Takeuchi, J. (2012). Botnet detection based on non-negative matrix factorization and the MDL principle. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7667 LNCS, pp. 400–409). https://doi.org/10.1007/978-3-642-34500-5_48
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