Abstract
The malware (malicious software) identification has to be supported by a comprehensive and extensive analysis of data from the Internet, and it is a hot topic nowadays. Data mining methods are commonly used techniques for identification of malicious software. Multi-source and multi-layered nature of propagation of malware assumes the utilization of data from heterogeneous data sources, i.e., data taken from various databases collecting samples from multiple layers of the network ISO/OSI reference model. Unfortunately, analysis of such multi-dimensional data sets is complex and often impossible task. In this paper we investigate multi-dimensionality reduction approach based on rough set analysis.
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Kruczkowski, M., Miciak, M. (2019). The Rough Set Analysis for Malicious Web Campaigns Identification. In: Choraś, M., Choraś, R. (eds) Image Processing and Communications Challenges 10. IP&C 2018. Advances in Intelligent Systems and Computing, vol 892. Springer, Cham. https://doi.org/10.1007/978-3-030-03658-4_25
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DOI: https://doi.org/10.1007/978-3-030-03658-4_25
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