论文标题
回到现场WHOIS：用于使用历史数据集的IP地址归因服务
Back-to-the-Future Whois: An IP Address Attribution Service for Working with Historic Datasets
论文作者
论文摘要
研究人员和从业人员经常面临必须将IP地址归因于组织的问题。对于当前数据，使用WHOIS或其他数据库之类的服务相当简单。同样，对于历史数据，像成熟的NCC这样的几个实体提供了可访问历史记录的网站。但是，对于大规模网络测量工作，研究人员通常必须归因于数百万个地址。对于当前数据，Cymru团队提供了允许批量地址归因的大量WHOIS服务。但是，在撰写本文时，没有可用的服务允许IP地址的历史性批量归因。因此，在本文中，我们介绍和评估了我们的“回到现实Whois”服务，从而在基于Caida Routeviews聚集的日常粒度上允许在日常粒度上进行历史性批量归因。我们免费为社区提供这项服务，并分享我们的实施，以便研究人员可以自己运行实例。
Researchers and practitioners often face the issue of having to attribute an IP address to an organization. For current data this is comparably easy, using services like whois or other databases. Similarly, for historic data, several entities like the RIPE NCC provide websites that provide access to historic records. For large-scale network measurement work, though, researchers often have to attribute millions of addresses. For current data, Team Cymru provides a bulk whois service which allows bulk address attribution. However, at the time of writing, there is no service available that allows historic bulk attribution of IP addresses. Hence, in this paper, we introduce and evaluate our 'Back-to-the-Future whois' service, allowing historic bulk attribution of IP addresses on a daily granularity based on CAIDA Routeviews aggregates. We provide this service to the community for free, and also share our implementation so researchers can run instances themselves.
