DMDb: Uncovering Criminal Hacking on the Dark Web to Enhance Cyber Threat Intelligence Research

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dc.contributor.authorKwan, Wesley
dc.contributor.authorTakahashi, Lynn
dc.contributor.authorPham, Nathan
dc.contributor.authorSista, Apurva
dc.contributor.authorTran, Minh Khoi
dc.contributor.authorLee, Vincent
dc.contributor.authorWang, Siwen
dc.contributor.authorMarin, Ericsson
dc.date.accessioned2024-12-26T21:07:41Z
dc.date.available2024-12-26T21:07:41Z
dc.date.issued2025-01-07
dc.description.abstractThe emergence of the dark web has enabled hackers to anonymously exchange information and trade malware worldwide, exposing organizations to an unprecedented number of threats. Without visibility into this offensive base, defenders are often left to mitigate damage. While prior cyber-threat intelligence research has been valuable, it has been constrained by incomplete, outdated, and noisy datasets. In this paper, we detail our efforts to build a comprehensive repository that illuminates the current plans of cyber-attackers. We achieve this by designing and deploying DarkMiner, a system that regularly scrapes the Tor network to populate the DarkMiner Database (DMDb). DMDb offers researchers a structured criminal hacking data collection enhanced with non-textual fields and object change tracking capabilities. To show its potential, we present three case studies analyzing: 1) cyber threat market fluctuations, 2) image-based vendor attribution, and 3) software vulnerability targeting.
dc.format.extent10
dc.identifier.doi10.24251/HICSS.2025.475
dc.identifier.isbn978-0-9981331-8-8
dc.identifier.othereed6414c-a1b1-4a8e-bb9f-6dce5704f19f
dc.identifier.urihttps://hdl.handle.net/10125/109319
dc.relation.ispartofProceedings of the 58th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectCybercrime
dc.subjectdark web, database, hacking, scraping
dc.titleDMDb: Uncovering Criminal Hacking on the Dark Web to Enhance Cyber Threat Intelligence Research
dc.typeConference Paper
dc.type.dcmiText
prism.startingpage3947

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