NIApr 16, 2019
The Methods to Improve Quality of Service by Accounting Secure ParametersTamara Radivilova, Lyudmyla Kirichenko, Dmytro Ageiev et al.
A solution to the problem of ensuring quality of service, providing a greater number of services with higher efficiency taking into account network security is proposed. In this paper, experiments were conducted to analyze the effect of self-similarity and attacks on the quality of service parameters. Method of buffering and control of channel capacity and calculating of routing cost method in the network, which take into account the parameters of traffic multifractality and the probability of detecting attacks in telecommunications networks were proposed. The both proposed methods accounting the given restrictions on the delay time and the number of lost packets for every type quality of service traffic. During simulation the parameters of transmitted traffic (self-similarity, intensity) and the parameters of network (current channel load, node buffer size) were changed and the maximum allowable load of network was determined. The results of analysis show that occurrence of overload when transmitting traffic over a switched channel associated with multifractal traffic characteristics and presence of attack. It was shown that proposed methods can reduce the lost data and improve the efficiency of network resources.
CRApr 16, 2019
Decrypting SSL/TLS traffic for hidden threats detectionTamara Radivilova, Lyudmyla Kirichenko, Dmytro Ageyev et al.
The paper presents an analysis of the main mechanisms of decryption of SSL/TLS traffic. Methods and technologies for detecting malicious activity in encrypted traffic that are used by leading companies are also considered. Also, the approach for intercepting and decrypting traffic transmitted over SSL/TLS is developed, tested and proposed. The developed approach has been automated and can be used for remote listening of the network, which will allow to decrypt transmitted data in a mode close to real time.
STApr 10, 2019
Fractal Time Series Analysis of Social Network ActivitiesLyudmyla Kirichenko, Vitalii Bulakh, Tamara Radivilova
In the work, a comparative correlation and fractal analysis of time series of Bitcoin crypto currency rate and community activities in social networks associated with Bitcoin was conducted. A significant correlation between the Bitcoin rate and the community activities was detected. Time series fractal analysis indicated the presence of self-similar and multifractal properties. The results of researches showed that the series having a strong correlation dependence have a similar multifractal structure.