IDOS6-ICMPV6 BASED DDOS ATTACK DATASET

Future IPv6-based networks face a significant security challenge with ICMPv6 communications. An attacker uses ICMPV6 messages to saturate the target system and aims to implement a Denial of Service (DoS) or Distributed Denial of Service (DDoS) attack. A robust intrusion detection system is being developed by researchers to address these issues. Researchers have access to a restricted number of IPv6 datasets to construct a well-known intrusion detection system, however these datasets are not accessible to the public and only target on one kind of attack. In this study, we primarily concentrate on the development of a benchmark dataset that is labelled and reflects ICMPv6 traffic for intrusion detection systems which focus on DoS/DDoS assaults under IPv6. The proposed datasets met the requirements for a high-quality, diversified dataset, and their online accessibility ensures that researchers could apply the dataset for experimentations. Using a GNS3 network simulation tool, an IPv6 network is simulated and ICMPv6 traffic is produced for the dataset. [18]. The developed traffic comprises of both normal and attack ICMPv6 traffic, and the attack traffic in our dataset consists of 17 different attacks based on information from message flooding packets for Router Advertisement, Router Solicitation, Neighbor Advertisement, and Neighbor Solicitation.

未来基于互联网协议第6版（IPv6）的网络在互联网控制报文协议第6版（ICMPv6）通信方面面临严峻的安全挑战。攻击者可利用ICMPv6报文泛滥耗尽目标系统资源，意图实施拒绝服务（Denial of Service, DoS）或分布式拒绝服务（Distributed Denial of Service, DDoS）攻击。为应对此类问题，研究人员正研发高性能入侵检测系统。现有用于构建主流入侵检测系统的IPv6数据集数量有限，且均未对公众开放，同时仅针对单一攻击类型。本研究主要致力于开发一款带标注的基准数据集，该数据集可反映IPv6环境下针对DoS/DDoS攻击的入侵检测系统所需的ICMPv6流量特征。所提出的数据集满足高质量、多样化的数据集要求，且可在线获取，能够为研究人员开展实验提供支撑。本研究借助GNS3网络仿真工具搭建IPv6网络仿真环境，并生成用于构建数据集的ICMPv6流量[18]。所生成的流量包含正常ICMPv6流量与攻击ICMPv6流量两类；本数据集中的攻击流量基于路由公告（Router Advertisement）、路由请求（Router Solicitation）、邻居公告（Neighbor Advertisement）及邻居请求（Neighbor Solicitation）报文的泛洪数据包信息，涵盖17种不同的攻击类型。