The object of this study was the process of detecting anomalies in computer systems. The task to timely detect anomalies in computer systems was solved, based on a mathematical model underlying which is the criteria for uniformity of samples of input data. The necessity and possibility to devise a universal and at the same time scientifically based approach to tracking the states of the system were determined. Therefore, the purpose of this work was to develop a methodology for determining the general criterion of anomaly in the behavior of a computer system depending on the input data. This will increase the reliability of identifying the anomaly in the behavior of the system, which, in turn, should increase its safety. To solve the proble...
An approach to the analysis of HAL/S software is discussed. The approach, called anomaly detection, ...
In order to improve reliability and safety of computer control system, it is very important to detec...
We present and empirically analyze a machine-learning approach for detecting intrusions on individua...
This work proposes anomalous computer system behavior detection method based on probabilistic automa...
This work studies systems and methods for anomaly detection in computer networks. At first, basic ca...
In today’s world there is lots of data requiring automated processing: nobody can analyze and extrac...
In this paper, we consider the verification of the hypothesis in the research of computer incidents ...
The impact of an anomaly is domain-dependent. In a dataset of network activities, an anomaly can imp...
Nowadays, when multiple aspects of our life depend on complex cyber-physical systems, automated anom...
Anomaly detection algorithms solve the problem of identifying unexpected values in data sets. Such a...
This paper describes the design and implementation of a general-purpose anomaly detector for streami...
Dependable complex systems often operate under variable and non-stationary conditions, which require...
The method of identifying abnormal behavior of computer systems based on the Hurst exponent is exami...
Automatic anomaly detection is a major issue in various areas. Beyond mere detection, the identifica...
Computer-based systems are integral part of modern technology. In order to create a correct system, ...
An approach to the analysis of HAL/S software is discussed. The approach, called anomaly detection, ...
In order to improve reliability and safety of computer control system, it is very important to detec...
We present and empirically analyze a machine-learning approach for detecting intrusions on individua...
This work proposes anomalous computer system behavior detection method based on probabilistic automa...
This work studies systems and methods for anomaly detection in computer networks. At first, basic ca...
In today’s world there is lots of data requiring automated processing: nobody can analyze and extrac...
In this paper, we consider the verification of the hypothesis in the research of computer incidents ...
The impact of an anomaly is domain-dependent. In a dataset of network activities, an anomaly can imp...
Nowadays, when multiple aspects of our life depend on complex cyber-physical systems, automated anom...
Anomaly detection algorithms solve the problem of identifying unexpected values in data sets. Such a...
This paper describes the design and implementation of a general-purpose anomaly detector for streami...
Dependable complex systems often operate under variable and non-stationary conditions, which require...
The method of identifying abnormal behavior of computer systems based on the Hurst exponent is exami...
Automatic anomaly detection is a major issue in various areas. Beyond mere detection, the identifica...
Computer-based systems are integral part of modern technology. In order to create a correct system, ...
An approach to the analysis of HAL/S software is discussed. The approach, called anomaly detection, ...
In order to improve reliability and safety of computer control system, it is very important to detec...
We present and empirically analyze a machine-learning approach for detecting intrusions on individua...