RADS dataset

RADS is an anomaly detection system that utilizes time-series forecasting models like ARIMA to predict DDoS attacks in real-time. This system focuses on Software Defined Networks and aims to achieve real-time attack detection in such environments. This dataset contains the network flow information that was used to test the model. The topology was constructed using mininet and had four hosts connected to one switch. Traffic was generated using iperf commands among pairs of nodes in random.

RADS是一款异常检测系统，其借助诸如自回归积分滑动平均模型（ARIMA）这类时序预测模型，实现分布式拒绝服务（DDoS）攻击的实时预测。该系统聚焦软件定义网络（SDN）场景，旨在在此类环境中实现实时攻击检测。本数据集包含用于测试该模型的网络流量信息。实验拓扑基于迷你网络（Mininet）搭建，由4台主机连接至1台交换机组成。研究人员在各节点对之间通过iperf命令随机生成网络流量。