Wavelet-analysis of network traffic time-series for detection of attacks on digital production infrastructurea

• Main Authors: Lavrova Darya, Semyanov Pavel, Shtyrkina Anna, Zegzhda Peter
• Format: Article
• Language: English
• Published: EDP Sciences 2018-01-01
• Series: SHS Web of Conferences
• Online Access: https://doi.org/10.1051/shsconf/20184400052

Digital production integrates with all the areas of human activity including critical industries, therefore the task of detecting network attacks has a key priority in protecting digital manufacture systems. This article offers an approach for analysis of digital production security based on evaluation of a posteriori probability for change point in time-series, which are based on the change point coefficient values of digital wavelet-transform in the network traffic time-series. These time-series make it possible to consider the network traffic from several points of view at the same time, which plays an important role in the task of detecting network attacks. The attack methods vary significantly; therefore, in order to detect them it is necessary to monitor different values of various traffic parameters. The proposed method has demonstrated its efficiency in detecting network service denial attacks (SlowLoris and HTTP DoS) being realized at the application level.