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Yuri Monakhov

Publications and source records attributed to Yuri Monakhov.

7 recordsLinked to original sources

A Machine-Synesthetic Approach To DDoS Network Attack Detection

In the authors' opinion, anomaly detection systems, or ADS, seem to be the most perspective direction in the subject of attack detection, because these systems can detect, among others, the unknown (zero-day) attacks. To detect anomalies, the authors propose to use machine synesthesia. In this case, machine synesthesia is understood as an interface that allows using image classification algorithms in the problem of detecting network anomalies, making it possible to use non-specialized image detection methods that have recently been widely and actively developed. The proposed approach is that the network traffic data is "projected" into the image. It can be seen from the experimental results that the proposed method for detecting anomalies shows high results in the detection of attacks. On a large sample, the value of the complex efficiency indicator reaches 97%.

cs.CV

Analysis Of Congestion Control In Data Channels With Frequent Frame Loss

Development of optimal control procedures for congested networks is a key factor in maintaining efficient network utilization. The absence of congestion control mechanism or its failure can lead to the lack of availability for certain network segments, and in severe cases -- for the entire network. The paper presents an analytical model describing the operation of the TCP Reno congestion control algorithm in terms of differential calculus and queuing systems. The purpose of this research is to explore the possibilities and ways of increasing the virtual channel capacity utilization efficiency in a lossy environment.

cs.NI

Simulation Model Of Functional Stability Of Business Processes

Functioning of business processes of high-tech enterprise is in a constant interaction with the environment. Herewith a wide range of such interaction represents a variety of conflicts affecting the achievement of the goals of business processes. All these things lead to the disruption of functioning of business processes. That's why modern enterprises should have mechanisms to provide a new property of business processes - ability to maintain and/or restore functions in various adverse effects. This property is called functional stability of business processes (FSBP). In this article we offer, showcase and test the new approach to assessing the results of business process re-engineering by simulating their functional stability before and after re-engineering.

cs.OH

About the survey of propagandistic messages in contemporary social media

This paper presents the research results that have identified a set of characteristic parameters of propagandistic messages. Later these parameters can be used in the algorithm creating special user-oriented propagandistic messages to improve distribution and assimilation of information by users.

cs.SI

Stochastic Models of Misinformation Distribution in Online Social Networks

This report contains results of an experimental study of the distribution of misinformation in online social networks (OSNs). We consider the classification of the topologies of OSNs and analyze the parameters identified in order to relate the topology of a real network with one of the classes. We propose an algorithm for conducting a search for the percolation cluster in the social graph.

cs.SI

Analytical model of misinformation of a social network node

This paper presents the research of the influence of cognitive, behavioral, representational factors on the susceptibility of the participants in social networks to misinformation, as well as on the activity of the nodes in this regard. The importance of this research consists of method of blocking the propaganda. This is very important because when people involuntarily acquire information some of them experience an undesired change in their social attitude. Such phenomena typically lead towards the information warfare. A model was developed during this research for calculating the level of misinformation of the social network participant (network node) based on the model of iterative learning process.

cs.SI