Interconnection Between Darknets

Cilleruelo, Carlos; de‐Marcos, Luis; Junquera-Sánchez, Javier; Martínez-Herráiz, José-Javier

doi:10.1109/mic.2020.3037723

Cited by 9 publications

(6 citation statements)

References 17 publications

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“…The graph in their work was related to the similarity of the site structure and was not a hyperlink-related graph. Cilleruelo et al [26] created a graph structure of the dark web network to clarify the connection between Tor and the I2P network. They analyzed data from the Ahmia [27] and DUTA-10K datasets [28], dark web crawling, and a total of 46 K addresses obtained from hidden service descriptors.…”

Section: Related Workmentioning

confidence: 99%

“…During the two years since we started observing the dark web, the number of nodes in the dark web network continued to grow, and from June 2018 to May 2020, the dark web became more diverse 22, 23,24,25,26). (link collection / search engine / markets / forums / hosting / porn) and complex.…”

Section: Observed Dark Web Sizementioning

confidence: 99%

“…Measuring the size of the dark web is considered difficult [26]. We estimated the number of dark web nodes from the observational data using the popular mark-recapture method in population ecology (Figure 12).…”

Section: Estimated Dark Web Sizementioning

confidence: 99%

See 2 more Smart Citations

Graph visualization of dark web hyperlinks and their feature analysis

Aoki

Goto

2021

IJNC

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Content regarding various illegal activities, such as weapon and drug trafficking, is shared on the dark web. Most of the illegal content is distributed on anonymous networks that cannot be directly accessed from the World Wide Web. A number of studies have been conducted on the network structure of the World Wide Web since its advent. Similar to the World Wide Web, the dark web is connected by hypertext transfer protocol (http); this makes it possible to use the methods developed for the web in the dark web. Many studies have investigated the dark web and its network structure. However, few studies have focused on the visualization of the dark web network structure, and there have been no studies investigating the temporal changes in the network structure.In this study, to understand the hypertext markup language (html) network structure of the dark web, we created and visualized a graph of the html hyperlink relations of the Tor network, which is popular on the dark web. We then compared the insights gained from graph centrality metrics with those gained from visualizations. The analyzed dataset comprised 25,270,157 pages of html text files crawled from the Tor network by breadth-first search from June 1, 2018, to January 30, 2021. Subsequently, we acquired half-yearly snapshots from the collected data and investigated the change in the dark web network over time using a time-series graph. Then, we derived the centrality metrics from the created graph data and confirmed the differences between the centrality metrics and visualizations. The results obtained in this study provided new insights into the dark web. First, we found that the dark web fluctuated significantly; the structure of the dark web network was more strongly interconnected. Second, most of the nodes that had increased in the past two years may have disappeared rapidly after May 2020. Third, analysis of each snapshot revealed that the proportion of highly volatile domains increased from 40% to 75% during the observation period. Fourth, after calculating the network centrality metrics from each snapshot and comparing the transition of hub nodes in chronological order, we observed that the importance of link-collection sites as the main information retrieval method used in the dark web decreased. Finally, we estimated the size of the dark web based on our observed dark web measurements using the mark-recapture method. To the best of our 354 International Journal of Networking and Computing knowledge, this is the first study to use the mark-recapture method to estimate the size of the dark web network.

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Section: Related Workmentioning

confidence: 99%

Section: Observed Dark Web Sizementioning

confidence: 99%

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Graph visualization of dark web hyperlinks and their feature analysis

Aoki

Goto

2021

IJNC

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“…Note that I2P can also be used to access the Surface Web. Cilleruelo et al [4] analyzed the connection between the Tor and I2P networks by looking at the darknet services. They found Tor and I2P operate as an ecosystem and there are clear paths between them.…”

Section: Related Workmentioning

confidence: 99%

“…The number of users is an indicator of how well the ecosystem is doing. Moving on to Total number of active projects (4). The greater the number of active projects, the higher the survival chances of an ecosystem.…”

Section: Step 3 -Select Metricsmentioning

confidence: 99%

Assessing the Health of the Dark Web:

Onyango

Steenvoorden

Scholten

et al. 2021

Agile Processes in Software Engineering and Extreme Programming – Workshops

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A hidden part of the World Wide Web is known as the Dark Web, featuring websites that cannot be indexed by traditional search engines. Many open source software products are used to access and navigate through the Dark Web. Together they form the Dark Web open source software ecosystem. Research on this ecosystem is scarce and research on the ecosystem health is non-existent, even though ecosystem health is an useful indicator of the livelihood of an ecosystem. The goal of this research is to evaluate the health of the ecosystem through an assessment of Tor, I2P and GitHub. The Open Source Ecosystem Health Operationalization framework is used to help perform this assessment. Eight metrics from the framework are selected, which are measured using the data collected. Analysis of Tor and I2P metrics suggest that there has been an increase in Tor and I2P user activity in the recent past. Added knowledge, spin offs and forks and usage indicate active participation and interest in Tor and I2P. There has also been an increase in the number of active GitHub Dark Web projects. However, these GitHub projects are not well-connected and only a small number of projects have a large number of contributors. There is some variety among the GitHub software projects. The framework proves to be adequately capable of determining the health of the Dark Web open source ecosystem with the available data.

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