Community anchor institutions (CAIs), such as libraries, schools, and community centers, are critical for providing Internet access to un- or under-served individuals and communities. Because many of these institutions are themselves under-provisioned, analyzing the reliability and quality of their Internet service is important. Doing so at scale requires knowing the IP addresses of these institutions so that broadband measurement and policy evaluation can occur. Unfortunately, these IPs are not systematically documented. As a first step towards widespread, scalable evaluation of CAI Internet connectivity, this paper presents Reverse IP Geolocation (RG), a new framework to infer IP addresses from physical address data. A key insight is that CAI street addresses are publicly known, which allows us to identify a candidate set of IPs from commercial geolocation that are likely serving the location associated with a CAI. In this paper, \textbf{we focus on US public libraries}, which offer both geographic diversity across thousands of locations, and some publicly available institutional records (\eg{}WHOIS registrations) that enable systematic validation of our approach. Our approach offers a novel integration of IP geolocation databases, DNS PTR records, WHOIS registrations, broadband provider data, and active measurements to identify IPs likely assigned to libraries and validate them. Based on evaluations, our approach can map a library to its IP prefix approx. half of the time, with coverage across all US states, as well as urban and rural areas. Our results highlight the feasibility of mapping CAI presence in IP space and offer a foundation for large-scale, remote broadband infrastructure evaluation.

翻译：社区锚定机构（如图书馆、学校和社区中心）对于向未获得或服务不足的个人和社区提供互联网接入至关重要。由于许多此类机构自身资源匮乏，分析其互联网服务的可靠性和质量具有重要意义。大规模开展此类工作需获知这些机构的IP地址，从而实现宽带测量与政策评估。然而，这些IP地址并未被系统性地记录。作为对CAI互联网连接进行广泛、可扩展评估的第一步，本文提出反向IP地理定位（RG）——一种从物理地址数据推断IP地址的新框架。关键洞察在于：CAI的街道地址是公开可查的，这使得我们能够从商业地理定位数据中识别出可能服务于该CAI关联位置的候选IP集。本文聚焦美国公共图书馆，其地理位置覆盖广泛（数千个地点），且部分公开机构记录（如WHOIS注册信息）可支持系统验证。我们的方法创新性地整合了IP地理定位数据库、DNS PTR记录、WHOIS注册信息、宽带提供商数据及主动测量手段，以识别可能分配给图书馆的IP地址并进行验证。评估表明，该方法约半数情况下可将图书馆映射至其IP前缀，且覆盖美国全部州份及城乡地区。研究结果凸显了在IP空间中映射CAI存在的可行性，并为大规模远程宽带基础设施评估奠定了基础。