학술논문

LVQ models of DDOS attacks identification
Document Type
Conference
Source
2018 14th International Conference on Advanced Trends in Radioelecrtronics, Telecommunications and Computer Engineering (TCSET) Advanced Trends in Radioelecrtronics, Telecommunications and Computer Engineering (TCSET), 2018 14th International Conference on. :510-513 Feb, 2018
Subject
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Fields, Waves and Electromagnetics
Photonics and Electrooptics
Signal Processing and Analysis
Computer crime
Neurons
IP networks
Entropy
Neural networks
Telecommunication traffic
Microsoft Windows
cybersecurity
information security
model identification DDoS attacks
neural network model)
Language
Abstract
Cyber security management of systems in the cyberspace has been a challenging problem for both practitioners and the research community. Their proprietary nature along with the complexity renders traditional approaches rather insufficient and creating the need for the adoption of a holistic point of view. In this paper describe approaches to synthesis of the identification models based on LVQ neural networks. The results of research testify to the prospects of work in this direction.