计算机科学
OpenFlow
模块化设计
控制器(灌溉)
阻塞(统计)
人工智能
异常检测
机器学习
随机森林
块(置换群论)
数据挖掘
大数据
分布式计算
软件定义的网络
计算机网络
嵌入式系统
控制(管理)
深度学习
交通分类
网络硬件
支持向量机
主动学习(机器学习)
作者
Víctor Carneiro,Marco Antonio Álvarez,Fidel Cacheda-Seijo
出处
期刊:SoftwareX
[Elsevier BV]
日期:2025-10-01
卷期号:32: 102382-102382
标识
DOI:10.1016/j.softx.2025.102382
摘要
SDN-CF (Software-Defined Network - Classification Framework) is a modular Java-based application built on the Northbound API of the ONOS Software-Defined Network (SDN) controller for network traffic analysis using machine learning techniques. While it employs the Random Forest algorithm by default, its open design allows the integration of alternative classifiers. SDN-CF enables the dynamic blocking of unwanted connections and generates an annotated dataset of OpenFlow traffic, supporting reproducible research in anomaly detection. Designed for academic and experimental use in virtualized environments, the tool fosters the evaluation and development of novel detection approaches in SDN contexts.
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