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Article . 2025
License: CC BY
Data sources: Datacite
ZENODO
Article . 2025
License: CC BY
Data sources: Datacite
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Crypto Crimes and the Invisible Economy: A Criminological Study of Bitcoin-Linked Offences

Authors: Laiqa Mustafa;

Crypto Crimes and the Invisible Economy: A Criminological Study of Bitcoin-Linked Offences

Abstract

This study explores the criminological dimensions of Bitcoin-linked crimes within the broader context of the invisible digital economy. As cryptocurrencies operate with decentralized and pseudonymous features, they have become attractive tools for illicit financial activities, including money laundering, ransomware attacks, darknet market transactions, and fraud. Using a qualitative approach and secondary analysis of existing literature, reports, and cybercrime data, this research identifies the patterns, motivations, and regulatory challenges associated with crypto-based offenses. It highlights how the anonymity and global reach of Bitcoin complicate law enforcement's ability to trace financial flows and enforce accountability. The study concludes by proposing policy interventions such as improved blockchain analytics, international regulatory cooperation, and public awareness strategies. The findings contribute to contemporary criminological discourse on emerging digital economies and cyber-enabled crime.

Keywords

Bitcoin, Crypto Crimes, Darknet Economy, Money Laundering, Cybercrime, Blockchain Regulatio

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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