Add to ORKGA method for detecting denial-of-service attacks on web applications based on the use of a multi-layer perceptron is considered. The main issues related to the use of the neural network are described: the process of collecting and preparing statistical data, the features of forming indicators that characterize the state of the web application, as well as the issues of training and evaluating the quality of the neural network
AbstractThe potential damage to computer networks keeps increasing due to a growing reliance on the ...
Abstract. In this paper, we present an approach for detecting and classifying attacks in computer ne...
The key objective of a Distributed Denial of Service (DDoS) attack is to compile multiple systems ac...
A solo attack may cause a big loss in computer and network systems, its prevention is, therefore, ve...
The article discusses the experience of using artificial neural networks to detect low-intensity (lo...
In this paper we introduce an intrusion detection system for Denial of Service (DoS) attacks against...
Purpose. The article is aimed at the development of a methodology for detecting attacks on a compute...
Purpose. Currently, there appear more often the reports of penetration into computer networks and at...
The prevention of any type of cyber attack is indispensable because a single attack may break the se...
The emergent damage to computer network keeps increasing due to an extensive and prevalent connectiv...
Penetration testing is conducted to detect and further to fix the security problems of the Web appli...
The possibility of applying machine learning for the classification of malicious requests to aWeb ap...
© International Research Publication House This paper discusses the concept and problem of detecting...
This bachelor thesis is focused on anomaly detection represented as computer network attacks by neur...
Neural network help to determine the network attack such as Denial of Service (DoS), User to Root (U...
AbstractThe potential damage to computer networks keeps increasing due to a growing reliance on the ...
Abstract. In this paper, we present an approach for detecting and classifying attacks in computer ne...
The key objective of a Distributed Denial of Service (DDoS) attack is to compile multiple systems ac...
A solo attack may cause a big loss in computer and network systems, its prevention is, therefore, ve...
The article discusses the experience of using artificial neural networks to detect low-intensity (lo...
In this paper we introduce an intrusion detection system for Denial of Service (DoS) attacks against...
Purpose. The article is aimed at the development of a methodology for detecting attacks on a compute...
Purpose. Currently, there appear more often the reports of penetration into computer networks and at...
The prevention of any type of cyber attack is indispensable because a single attack may break the se...
The emergent damage to computer network keeps increasing due to an extensive and prevalent connectiv...
Penetration testing is conducted to detect and further to fix the security problems of the Web appli...
The possibility of applying machine learning for the classification of malicious requests to aWeb ap...
© International Research Publication House This paper discusses the concept and problem of detecting...
This bachelor thesis is focused on anomaly detection represented as computer network attacks by neur...
Neural network help to determine the network attack such as Denial of Service (DoS), User to Root (U...
AbstractThe potential damage to computer networks keeps increasing due to a growing reliance on the ...
Abstract. In this paper, we present an approach for detecting and classifying attacks in computer ne...
The key objective of a Distributed Denial of Service (DDoS) attack is to compile multiple systems ac...