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

2026-05-14

AI Summary

This study investigates whether node selection in the I2P network is influenced by geographic location and the potential implications for anonymity and performance. Through empirical analysis of the topology comprising 327 routers and 254 connections, it presents the first systematic examination of the relationship between geographic distribution and routing choices in real-world I2P deployments. Applying network science methods—including assortativity analysis, community detection, and permutation tests—the study finds negligible geographic homophily (r = 0.017, p = 0.222), with intra-country link proportions aligning closely with random expectations. Although the network exhibits high modularity in its community structure, geographic alignment remains only moderate (NMI = 0.521). These findings reveal that I2P displays a highly heterogeneous and nearly random geographic mixing pattern, offering crucial empirical insights into its anonymity mechanisms.

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.

Problem

• I2P
• peer selection
• geographic homophily
• network topology
• anonymity

Innovation

• geographic homophily
• peer selection
• network topology
• anonymity
• I2P