The use of artificial intelligence (AI) has the potential to be highly effective in detecting and monitoring illegal trafficking of cultural heritage (CH) goods through image classification techniques, particularly on online marketplaces where the trade of stolen CH objects has become a major global issue. Traditional investigation methods are no longer adequate, but with the assistance of AI, law enforcement agencies and CH organizations can now boost monitoring capabilities to detect, track, and possibly recover stolen objects more efficiently. AI algorithms can indeed analyze images to identify unique features and characteristics that can be used to determine their authenticity and provenance. Additionally, AI can detect patterns and networks of illicit trafficking, and link stolen objects to their places of origin, facilitating the recovery process. In this context, the SIGNIFICANCE project (Stop Illicit Heritage Trafficking with Artificial Intelligence) has been specifically designed to increase the response capabilities of public authorities and police corps against the illicit trafficking of cultural goods perpetrated through internet channels (i.e., social platforms, web, and dark web). By leveraging the power of Deep Learning (DL), AI can help prevent the loss of invaluable cultural artifacts and ensure that they are returned to their rightful owners and places of origin. This paper presents the results reached by the SIGNIFICANCE AI framework on image datasets collected over the web and social media through crawling algorithms.

ARTIFICIAL INTELLIGENCE TO FIGHT ILLICIT TRAFFICKING OF CULTURAL PROPERTY / Abate, D.; Agapiou, A.; Toumbas, K.; Lampropoulos, A.; Petrides, K.; Pierdicca, R.; Paolanti, M.; Di Stefano, F.; Felicetti, A.; Malinverni, E. S.; Zingaretti, P.. - In: INTERNATIONAL ARCHIVES OF THE PHOTOGRAMMETRY, REMOTE SENSING AND SPATIAL INFORMATION SCIENCES. - ISSN 2194-9034. - XLVIII-M-2-2023:(2023), pp. 3-10. (Intervento presentato al convegno Documenting, Understanding, Preserving Cultural Heritage. Humanities and Digital Technologies for Shaping the Future tenutosi a Firenze, Italy nel 25-30 Giugno 2023) [10.5194/isprs-archives-XLVIII-M-2-2023-3-2023].

ARTIFICIAL INTELLIGENCE TO FIGHT ILLICIT TRAFFICKING OF CULTURAL PROPERTY

Pierdicca, R.;Di Stefano, F.;Felicetti, A.;Malinverni, E. S.;Zingaretti, P.
2023-01-01

Abstract

The use of artificial intelligence (AI) has the potential to be highly effective in detecting and monitoring illegal trafficking of cultural heritage (CH) goods through image classification techniques, particularly on online marketplaces where the trade of stolen CH objects has become a major global issue. Traditional investigation methods are no longer adequate, but with the assistance of AI, law enforcement agencies and CH organizations can now boost monitoring capabilities to detect, track, and possibly recover stolen objects more efficiently. AI algorithms can indeed analyze images to identify unique features and characteristics that can be used to determine their authenticity and provenance. Additionally, AI can detect patterns and networks of illicit trafficking, and link stolen objects to their places of origin, facilitating the recovery process. In this context, the SIGNIFICANCE project (Stop Illicit Heritage Trafficking with Artificial Intelligence) has been specifically designed to increase the response capabilities of public authorities and police corps against the illicit trafficking of cultural goods perpetrated through internet channels (i.e., social platforms, web, and dark web). By leveraging the power of Deep Learning (DL), AI can help prevent the loss of invaluable cultural artifacts and ensure that they are returned to their rightful owners and places of origin. This paper presents the results reached by the SIGNIFICANCE AI framework on image datasets collected over the web and social media through crawling algorithms.
2023
File in questo prodotto:
File Dimensione Formato  
isprs-archives-XLVIII-M-2-2023-3-2023.pdf

accesso aperto

Tipologia: Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza d'uso: Creative commons
Dimensione 2.99 MB
Formato Adobe PDF
2.99 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11566/325573
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? ND
social impact