活跃IP地址数据集

活跃IP地址数据集主要面向互联网地址空间活跃性分析、网络资产发现与网络拓扑研究需求建设，基于全球10个分布式阿里云VPS探测站点（新加坡、上海、深圳、法兰克福、迪拜、香港、东京、弗吉尼亚、伦敦、硅谷）的ZMap主动探测平台产生。主要记录了响应ICMP、TCP（30个常见端口）、UDP、DNS、NTP、RIPE Atlas等协议探测的IPv4地址、IPv6地址、IPv6前缀等观测项，覆盖2025年10月的周度探测数据，时间精度为日级，空间精度为地址或前缀级。该数据集采用DHC（分裂式层次聚类）算法进行动态资源分配，实现90%内存开销降低，数据项约58.98 GiB，包含151个对象文件，涵盖IPv4与IPv6双栈地址空间。本数据集为掌握全球互联网地址空间使用状况、支持网络测量研究、辅助网络安全态势感知提供了重要的基础数据资源。This Active IP Address Dataset was developed to meet the requirements of Internet address space activity analysis, network asset discovery and network topology research. It is generated using the ZMap active probing platform deployed across 10 distributed Alibaba Cloud VPS probing sites worldwide, including Singapore, Shanghai, Shenzhen, Frankfurt, Dubai, Hong Kong, Tokyo, Virginia, London, and Silicon Valley. The dataset mainly records observation items such as IPv4 addresses, IPv6 addresses, and IPv6 prefixes detected in response to probing via protocols including ICMP, TCP (30 common ports), UDP, DNS, NTP, and RIPE Atlas. It covers weekly probing data collected in October 2025, with a temporal precision at the day level and a spatial precision at the address or prefix level. This dataset adopts the DHC (Divisive Hierarchical Clustering) algorithm for dynamic resource allocation, achieving a 90% reduction in memory overhead. The total data size is approximately 58.98 GiB, consisting of 151 object files, and covers both IPv4 and IPv6 dual-stack address spaces. This dataset serves as an essential foundational data resource for grasping the usage status of global Internet address spaces, supporting network measurement research, and assisting network security situational awareness.

搜集汇总

背景与挑战

背景概述

该数据集面向互联网地址空间活跃性分析、网络资产发现与网络拓扑研究，基于全球10个分布式探测站点的ZMap主动探测平台生成，记录响应ICMP、TCP等协议探测的IPv4与IPv6地址信息，覆盖2025年10月的周度数据。数据量约58.98 GiB，包含151个对象文件，采用DHC算法降低内存开销，为网络测量研究和网络安全态势感知提供基础数据资源。