arXiv subjects

Syed Tauhidun Nabi

Publications and source records attributed to Syed Tauhidun Nabi.

2 recordsLinked to original sources

arXiv2026

Lost in the Prefix: Revisiting IP Geolocation Accuracy Across Networks and Geographies

IP geolocation databases are widely used in research, policy, and industry, yet their accuracy across network types and geographies remains poorly characterized. We present a large scale evaluation of four major providers (MaxMind GeoLite2, IPinfo, IP2Location, and DB-IP) using ground truth from RIPE Atlas and UNICEF Giga across 175 countries. We find that mobile networks exhibit median errors more than 10 times higher than fixed networks across all providers (179--207~km vs.\ 3--16~km), and that Global South regions show significantly higher failure rates than Global North: Asia exceeds 53--61\% and Africa 66--72\%, compared to 9--20\% in Europe. We trace both gaps to a shared structural source: provider prefixes in mobile networks and Global South geographies are more likely to be coarser than BGP announcements, and approximately 70\% of mobile prefixes span more than 100~km geographically. Our findings point to prefix granularity as a common explanatory factor: coarser prefixes consistently produce the highest errors regardless of provider, network type, or geography.

cs.NI↗

arXiv2024

Red is Sus: Automated Identification of Low-Quality Service Availability Claims in the US National Broadband Map

The FCC's National Broadband Map aspires to provide an unprecedented view into broadband availability in the US. However, this map, which also determines eligibility for public grant funding, relies on self-reported data from service providers that in turn have incentives to strategically misrepresent their coverage. In this paper, we develop an approach for automatically identifying these low-quality service claims in the National Broadband Map. To do this, we develop a novel dataset of broadband availability consisting of 750k observations from more than 900 US ISPs, derived from a combination of regulatory data and crowdsourced speed tests. Using this dataset, we develop a model to classify the accuracy of service provider regulatory filings and achieve AUCs over 0.98 for unseen examples. Our approach provides an effective technique to enable policymakers, civil society, and the public to identify portions of the National Broadband Map that are likely to have integrity challenges.

cs.NI↗