Visible to the public Analysis of Cybersecurity Threats in Cloud Applications Using Deep Learning Techniques

TitleAnalysis of Cybersecurity Threats in Cloud Applications Using Deep Learning Techniques
Publication TypeConference Paper
Year of Publication2019
AuthorsSokolov, S. A., Iliev, T. B., Stoyanov, I. S.
Conference Name2019 42nd International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO)
ISBN Number978-953-233-098-4
Keywordscloud applications, cloud computing, cloud environments, cybersecurity, cybersecurity threats, Deep Learning, deep learning techniques, deep neural networks, enterprise applications, enterprise grade security applications, IDS, learning (artificial intelligence), Measurement, Metrics, neural nets, privacy, pubcrawl, security of data, Support vector machines, telecommunications equipment, threat vectors
Abstract

In this paper we present techniques based on machine learning techniques on monitoring data for analysis of cybersecurity threats in cloud environments that incorporate enterprise applications from the fields of telecommunications and IoT. Cybersecurity is a term describing techniques for protecting computers, telecommunications equipment, applications, environments and data. In modern networks enormous volume of generated traffic can be observed. We propose several techniques such as Support Vector Machines, Neural networks and Deep Neural Networks in combination for analysis of monitoring data. An approach for combining classifier results based on performance weights is proposed. The proposed approach delivers promising results comparable to existing algorithms and is suitable for enterprise grade security applications.

URLhttps://ieeexplore.ieee.org/abstract/document/8756755
DOI10.23919/MIPRO.2019.8756755
Citation Keysokolov_analysis_2019