Detection of DDoS (Distributed Denial of Service) traffic is of great importance for the availability protection of services and other information and communication resources. The research presented in this paper shows the application of artificial neural networks in the development of detection and classification model for three types of DDoS attacks and legitimate network traffic. Simulation results of developed model showed accuracy of 95.6% in classification of pre-defined classes of traffic
Currently high-speed networks have been attacked by successive waves of Distributed Denial of Servic...
Abstract- DDoS attacks temporarily make the target system unavailable to the legitimate users. They ...
In this paper we introduce an intrusion detection system for Denial of Service (DoS) attacks against...
The key objective of a Distributed Denial of Service (DDoS) attack is to compile multiple systems ac...
Distributed Denial-of-Service (DDoS) is one of network attack technique which increased every year, ...
Distributed denial of service attack classified as a structured attack to deplete server, sourced fr...
Abstract- A distributed denial-of-service (DDoS) attack is one in which a large number of compromise...
This bachelor thesis is focused on anomaly detection represented as computer network attacks by neur...
The article discusses the experience of using artificial neural networks to detect low-intensity (lo...
The paper discusses the concept and problem of identifying DDoS attacks for information management. ...
Nowadays, the small-medium enterprises security against cyber-attacks is a matter of great importanc...
Internet of Things (IoT) is an architecture that connects large numbers of smart devices in today's ...
Massive information has been transmitted through complicated network connections around the world. T...
NoTraffic anomalies caused by Distributed Denial-of-Service (DDoS) attacks are major threats to both...
DDoS attacks are a major Internet security concern with this large number of customers. Each attack ...
Currently high-speed networks have been attacked by successive waves of Distributed Denial of Servic...
Abstract- DDoS attacks temporarily make the target system unavailable to the legitimate users. They ...
In this paper we introduce an intrusion detection system for Denial of Service (DoS) attacks against...
The key objective of a Distributed Denial of Service (DDoS) attack is to compile multiple systems ac...
Distributed Denial-of-Service (DDoS) is one of network attack technique which increased every year, ...
Distributed denial of service attack classified as a structured attack to deplete server, sourced fr...
Abstract- A distributed denial-of-service (DDoS) attack is one in which a large number of compromise...
This bachelor thesis is focused on anomaly detection represented as computer network attacks by neur...
The article discusses the experience of using artificial neural networks to detect low-intensity (lo...
The paper discusses the concept and problem of identifying DDoS attacks for information management. ...
Nowadays, the small-medium enterprises security against cyber-attacks is a matter of great importanc...
Internet of Things (IoT) is an architecture that connects large numbers of smart devices in today's ...
Massive information has been transmitted through complicated network connections around the world. T...
NoTraffic anomalies caused by Distributed Denial-of-Service (DDoS) attacks are major threats to both...
DDoS attacks are a major Internet security concern with this large number of customers. Each attack ...
Currently high-speed networks have been attacked by successive waves of Distributed Denial of Servic...
Abstract- DDoS attacks temporarily make the target system unavailable to the legitimate users. They ...
In this paper we introduce an intrusion detection system for Denial of Service (DoS) attacks against...