Volume 8 - Issue 3
Applying Big Data Processing and Machine Learning Methods for Mobile Internet of Things Security Monitoring
- Igor Kotenko
Laboratory of Computer Security Problems of St. Petersburg Institute for Informatics and Automation (SPIIRAS), 14-th line, 39, Saint-Petersburg, 199178, Russia, St. Petersburg National Research University of Information Technologies, Mechanics and Optics, 49, Kronverkskiy prospekt, Saint-Petersburg, Russia
ivkote@comsec.spb.ru
- Igor Saenko
Laboratory of Computer Security Problems of St. Petersburg Institute for Informatics and Automation (SPIIRAS), 14-th line, 39, Saint-Petersburg, 199178, Russia, St. Petersburg National Research University of Information Technologies, Mechanics and Optics, 49, Kronverkskiy prospekt, Saint-Petersburg, Russia
ibsaen@comsec.spb.ru
- Alexander Branitskiy
Laboratory of Computer Security Problems of St. Petersburg Institute for Informatics and Automation (SPIIRAS), 14-th line, 39, Saint-Petersburg, 199178, Russia, St. Petersburg National Research University of Information Technologies, Mechanics and Optics, 49, Kronverkskiy prospekt, Saint-Petersburg, Russia
branitskiy@comsec.spb.ru
Keywords: Big Data, Machine Learning, Security Monitoring, Mobile Security, Internet of Things, Classifier.
Abstract
The paper offers a new approach to Big Data processing for security monitoring of mobile Internet
of things elements based on machine learning and its implementation using parallel algorithms.
The architecture of security monitoring system is considered. It specifies several machine learning
mechanisms intended for solving classification tasks. The classifier operation results are exposed to
plurality voting, weight voting and soft voting. The experimental assessment of performance and
accuracy of the offered methods is made.