From Counterfeit Detection To Network Attribution: A Forensic-Intelligence Framework For Disrupting Illicit Supply Chains

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Yash Rahul Kalbhor, BBA. LL.B. (Hons), MIT-WPU School of Law Research Intern (CCSFI), Centre for Crime Sciences and Forensic Intelligence

ABSTRACT

Counterfeit enforcement is often dominated by seizure-led and authenticity- focused responses that identify fake goods without disrupting the production and distribution systems behind them. This article develops a forensic- intelligence framework for moving from counterfeit detection to network attribution. Drawing on forensic trace theory, supply-chain analysis, and criminal intelligence, it argues that counterfeit currency, forged security documents, and illicit consumer goods can be treated as data-bearing objects containing physical, chemical, mechanical, and digital traces of their production environments. When systematically documented, compared, and linked across seizures, these traces can support source hypotheses, identify production batches, and guide network mapping. However, attribution remains probabilistic and must be distinguished from proof of criminal guilt. The article therefore emphasises corroboration, chain of custody, alternative explanations, and evidentiary restraint. Its central contribution is a structured framework that connects object-level examination with linkage analysis, financial and logistical intelligence, and legally resilient disruption strategies.

Keywords: forensic attribution; counterfeit goods; criminal intelligence; forensic document examination; illicit supply chains; linkage analysis.

7. FROM COUNTERFEIT DETECTION TO NETWORK ATTRIBUTION- A FORENSIC-INTELLIGENCE FRAMEWORK FO

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