Vera Lukicheva
Vera Lukicheva has a total of 3 co-authors. Here are the top co-authors by number of shared publications:
- Andrey Privalov
Emperor Alexander I St. Petersburg State Transport University
2 shared publications - Igor Kotenko
St. Petersburg Federal Research Center of the Russian Academy of Sciences
2 shared publications - Igor Saenko
St. Petersburg Federal Research Center of the Russian Academy of Sciences, SPC RAS, St. Petersburg, Russia
1 shared publication
Latest Publications
- Open Access
Increasing the Sensitivity of the Method of Early Detection of Cyber-Attacks in Telecommunication Networks Based on Traffic Analysis by Extreme Filtering
The paper proposes a method for improving the accuracy of early detection of cyber attacks with a small impact, in which the mathematical expectation is a fraction of the total, and the pulse repetition period is quite long. Early detection of attacks against telecommunication networks is based on traffic analysis using extreme filtering. The algorithm of fuzzy logic for deciding on the results of extreme filtering is suggested. The results of an experimental evaluation of the proposed method are presented. They demonstrate that the method is sensitive even with minor effects. In order to eliminate the redundancy of the analyzed parameters, it is enough to use the standard deviation and the correlation interval for decision making.
Open AccessIncreasing the Sensitivity of the Method of Early Detection of Cyber-Attacks in Telecommunication Networks Based on Traffic Analysis by Extreme Filtering
The paper proposes a method for improving the accuracy of early detection of cyber attacks with a small impact, in which the mathematical expectation is a fraction of the total, and the pulse repetition period is quite long. Early detection of attacks against telecommunication networks is based on traffic analysis using extreme filtering. The algorithm of fuzzy logic for deciding on the results of extreme filtering is suggested. The results of an experimental evaluation of the proposed method are presented. They demonstrate that the method is sensitive even with minor effects. In order to eliminate the redundancy of the analyzed parameters, it is enough to use the standard deviation and the correlation interval for decision making.
- Open Access
Method of Early Detection of Cyber-Attacks on Telecommunication Networks Based on Traffic Analysis by Extreme Filtering
The paper suggests a method of early detection of cyber-attacks by using DDoS attacks as an example) using the method of extreme filtering in a mode close real time. The process of decomposition of the total signal (additive superposition of attacking and legitimate effects) and its decomposition using the method of extreme filtering is simulated. A profile model of a stochastic network is proposed. This allows to specify the influence of the intruder on the network using probabilistic-time characteristics. Experimental evaluation of metrics characterizing the cyber-attack is given. It is demonstrated how obtained values of metrics confirm the process of attack preparation, for instance the large-scaled telecommunication network, which includes the proposed method for early detection of attacks, has a recovery time of no more than 9 s, and the parameters of quality of service remain in an acceptable range.
Open AccessMethod of Early Detection of Cyber-Attacks on Telecommunication Networks Based on Traffic Analysis by Extreme Filtering
The paper suggests a method of early detection of cyber-attacks by using DDoS attacks as an example) using the method of extreme filtering in a mode close real time. The process of decomposition of the total signal (additive superposition of attacking and legitimate effects) and its decomposition using the method of extreme filtering is simulated. A profile model of a stochastic network is proposed. This allows to specify the influence of the intruder on the network using probabilistic-time characteristics. Experimental evaluation of metrics characterizing the cyber-attack is given. It is demonstrated how obtained values of metrics confirm the process of attack preparation, for instance the large-scaled telecommunication network, which includes the proposed method for early detection of attacks, has a recovery time of no more than 9 s, and the parameters of quality of service remain in an acceptable range.