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Conference object . 2026
License: CC BY
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Article . 2026
License: CC BY
Data sources: Datacite
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Article . 2026
License: CC BY
Data sources: Datacite
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Automated OSINT and Social Media Monitoring for Drug Activity Detection

Authors: Jaison, Athul; Thomas, Ann Mary;

Automated OSINT and Social Media Monitoring for Drug Activity Detection

Abstract

The expansion of digital communication technolo- gies has created new pathways for drug trafficking operations. Criminal networks increasingly use public social media platforms to promote their activities while they use encrypted messaging systems to maintain operational contact. The combination of distributed digital networks and hybrid digital networks cre- ates major obstacles for conventional methods of conducting investigations. The research paper investigates how artificial intelligence (AI) technology works together with Open-Source Intelligence (OSINT) methods to create automated systems that detect drug-related activities that occur online. The Narcotics Intelligence Platform aims to combine three technologies which include Natural Language Processing (NLP), computer vision, and network-based behavioral analytics. The article investigates the ethical and legal aspects which govern AI-based monitoring systems together with its associated governance structures. 

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Keywords

Artificial Intelligence, OSINT, Online Narcotics, NLP, Computer Vision, Encrypted Messaging, Dark Web, Cyber- crime Investigation, Artificial Intelligence, OSINT, Online Narcotics, NLP, Computer Vision, Encrypted Messaging, Dark Web, Cyber- crime Investigation

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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