Mapping the invisible internet: Framework and dataset

This article describes a novel dataset that maps the network layer of the Invisible Internet Project (I2P). The data was collected using SWARM-I2P framework, which deployed I2P routers as a network of mapping agents that gather information on the network's topology and traffic over an extended period. The dataset documents over 50,000 nodes, including subsets of high-performance (FastSet) nodes and high-capacity nodes characterized by metrics such as bandwidth, latency, and uptime. It also contains detailed records of network traffic and the geographic distribution of thousands of nodes. Data was collected using a combination of methods, including querying router consoles, analysing the network database (netDb), and passive network monitoring. All node identifiers were anonymized to maintain user privacy. The data is publicly available in CSV and TXT formats on Zenodo, with mapping scripts provided on GitHub. This resource provides a foundational understanding of the decentralized routing behaviours that underpin I2P's anonymity, making it suitable for reuse in analyses of tunnel node selection, anonymity network resilience, and adversarial modelling.

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Publication Details

Journal
Data in Brief
Published
2025-10-15
DOI
https://doi.org/10.1016/j.dib.2025.112175
Citations
3
Primary Topic
Internet Traffic Analysis and Secure E-voting
Type
article
Field-Weighted Citation Impact
7.44
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article

Mapping the invisible internet: Framework and dataset

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3 citations
Data in Brief
Internet Traffic Analysis and Secure E-voting
7.44
article

Mapping the invisible internet: Framework and dataset

Jacques Bou Abdo, Sunkanmi Oluwadare, Falah H. Hussein, Kemi Akanbi, Siddique Abubakr Muntaka, Michael Asante, Oliver Konyo
article en
3 citations

Abstract

This article describes a novel dataset that maps the network layer of the Invisible Internet Project (I2P). The data was collected using SWARM-I2P framework, which deployed I2P routers as a network of mapping agents that gather information on the network's topology and traffic over an extended period. The dataset documents over 50,000 nodes, including subsets of high-performance (FastSet) nodes and high-capacity nodes characterized by metrics such as bandwidth, latency, and uptime. It also contains detailed records of network traffic and the geographic distribution of thousands of nodes. Data was collected using a combination of methods, including querying router consoles, analysing the network database (netDb), and passive network monitoring. All node identifiers were anonymized to maintain user privacy. The data is publicly available in CSV and TXT formats on Zenodo, with mapping scripts provided on GitHub. This resource provides a foundational understanding of the decentralized routing behaviours that underpin I2P's anonymity, making it suitable for reuse in analyses of tunnel node selection, anonymity network resilience, and adversarial modelling.

Data in BriefVol. 63
Kwame Nkrumah University of Science and Technology (GH), University of Cincinnati (US), Garden City University College (GH)
Openalex Percentile: Top 3%
Internet Traffic Analysis and Secure E-voting
7.44
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