Abstract
The paper presents a comparative analysis of two schemes for combining the binary classifiers. In the role of such classifiers we use well-known models—support vector machines (SVMs). For constructing the multiclass models we experimentally investigate two schemes for combining the SVMs, namely a classification binary tree (CBT) and a directed acyclic graph (DAG). Main application of considered models we demonstrate in the paper is attack detection and classification in mobile Internet and networks. The various performance indicators of classifiers are given. The results of experiments performed for to estimate these indicators and usage of time and system resources are presented.
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This research is being supported by the grant of RSF #18-11-00302 in SPIIRAS.
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Branitskiy, A., Kotenko, I. (2019). Attack Detection in Mobile Internet and Networks Using the Graph-Based Schemes for Combining the Support Vector Machines. In: You, I., Chen, HC., Sharma, V., Kotenko, I. (eds) Mobile Internet Security. MobiSec 2017. Communications in Computer and Information Science, vol 971. Springer, Singapore. https://doi.org/10.1007/978-981-13-3732-1_1
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DOI: https://doi.org/10.1007/978-981-13-3732-1_1
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