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arXiv · 2605.14435

Geographic Patterns in I2P Peer Selection: An Empirical Network Topology Analysis

Siddique Abubakr Muntaka·Jess Kropczynski·Jacques Bou Abdo·Murat Ozer
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Abstract

The Invisible Internet Project (I2P) routes data via encrypted, decentralized tunnels. Peer selection can significantly affect security and performance. This empirical study examines whether geographic location systematically influences I2P's routing topology. Consistent with I2P's design principles, which include avoiding multiple peers from the same /16 IP subnet to maximize anonymity, we conducted assortativity analysis, community detection, and permutation testing on data from 327 routers and 254 connections (SWARM-I2P). We found a network-level absence of significant geographic homophily. The assortativity coefficient was r = 0.017 (p = 0.222). Same-country connections (11.1%) are statistically near random expectation (10.91%). Community detection found 110 highly modular groups (Q = 0.972) only moderately aligned geographically (NMI = 0.521). We conclude that aggregate peer selection in I2P leads to a highly heterogeneous, random geographical mixing, providing a foundation for understanding the performance-anonymity tradeoff.

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Siddique Abubakr Muntaka, Jess Kropczynski, Jacques Bou Abdo, Murat Ozer. 2026-05-14. Geographic Patterns in I2P Peer Selection: An Empirical Network Topology Analysis. https://arxiv.org/abs/2605.14435

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