Dizzy

Links

• Open website arxiv.org

Tags

1. 
   Dark Web Architecture Study

   This arXiv paper proposes an end-to-end scalable architecture for early identification of new Tor sites and daily analysis of their content. It is built on an open source big data stack including Kubernetes, Kafka, Kubeflow and MinIO, discovering onion addresses across several sources, downloading HTML from Tor, deduplicating with MinHash LSH and categorizing with BERTopic modeling. In 93 days it identified 80,049 onion services and characterized 90% of them.

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2. 
   Forbes SecureDrop

   Forbes SecureDrop is an open-source whistleblower submission system that media organizations such as Forbes use to securely accept documents from and communicate with anonymous sources. Users access the SecureDrop page through the Tor browser and follow instructions to send information. Users receive a codename to log back in and check for responses from Forbes reporters.

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3. 
   Topical Shifts in the Dark Web

   An arXiv paper presenting a longitudinal analysis of the dark web cybercrime ecosystem. The authors analyze 25,065 websites using 11,403,638 HTML snapshots collected over six years, applying a topic-modeling framework with domain-specific embeddings, density-based clustering and temporal aggregation. The analysis identifies 55 thematic clusters and measures topic prevalence and lifecycle at the website level.

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4. 
   Mimir Onion Study

   An arXiv paper presenting a large-scale analysis of the Tor network using a crawler called Mimir, which collects and visits linked content. The authors report a dataset of pages from more than 25k sites and examine network topology, replicated content and content types.

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5. 
   Monitoring the Dark Web

   A working paper by John Schriner that focuses on how researchers monitor the Dark Web. It defines onion services and Tor and discusses tools for monitoring and securing onion services.

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6. 
   Onion Service Honeypot Study

   An arXiv paper measuring onion website discovery and Tor users' interests with honeypots. The authors deployed honeypot onion websites in March–April 2025 and seeded links via three channels to observe interaction events. They report that human users almost without exception originated from Ahmia.fi, and that the CSAM-themed honeypot drew markedly higher engagement than the others.

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