Online Incremental Learning for High Bandwidth Network Traffic Classification
نویسندگان
چکیده
منابع مشابه
Generation of High Bandwidth Network Traffic Traces
High bandwidth network traffic traces are needed to understand the behavior of high speed networks (such as the Internet backbone). However, the implementation of a mechanism to collect such traces is difficult in practice. In the absence of real traces, tools to generate high bandwidth traces would aid the study of high speed network behavior. We describe three methods of generating high bandw...
متن کاملIncremental Online Learning in High Dimensions
Locally weighted projection regression (LWPR) is a new algorithm for incremental nonlinear function approximation in high-dimensional spaces with redundant and irrelevant input dimensions. At its core, it employs nonparametric regression with locally linear models. In order to stay computationally efficient and numerically robust, each local model performs the regression analysis with a small n...
متن کاملMachine Learning Classification of Malicious Network Traffic
1.1. Intrusion Detection Systems. In our society, information systems are everywhere. They are used by corporations to store proprietary and other sensitive data, by families to store financial and personal information, by universities to keep research data and ideas, and by governments to store defense and security information. It is very important that the information systems that house this ...
متن کاملOnline Network Traffic Classification Algorithm Based on RVM
Since compared with the Support Vector Machine (SVM), the Relevance Vector Machine (RVM) not only has the advantage of avoiding the overlearn which is the characteristic of the SVM, but also greatly reduces the amount of computation of the kernel function and avoids the defects of the SVM that the scarcity is not strong, the large amount of calculation as well as the kernel function must satisf...
متن کاملResearch on Online Game Traffic Classification Based on Machine Learning
This paper summarizes online game flow attributes by observing a great number of game data packets and computes their flow feature using Python programming language. Furthermore, we investigate several machine learning algorithms to classify five different online games automatically and correctly, that provide the average accuracy is over 80%. The test results show that machine learning has the...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Applied Computational Intelligence and Soft Computing
سال: 2016
ISSN: 1687-9724,1687-9732
DOI: 10.1155/2016/1465810