The widespread deployment of surveillance cameras has raised serious privacy concerns, and many privacy-enhancing schemes have been recently proposed to automatically redact images of selected individuals in the surveillance video for protection. Of equal importance are the privacy and efficiency of techniques to first, identify those individuals for privacy protection and second, provide access to original surveillance video contents for security analysis. In this paper, we propose an anonymous subject identification and privacy data management system to be used in privacy-aware video surveillance. The anonymous subject identification system uses iris patterns to identify individuals for privacy protection. Anonymity of the iris-matching process is guaranteed through the use of a garbled-circuit (GC)-based iris matching protocol. A novel GC complexity reduction scheme is proposed by simplifying the iris masking process in the protocol. A user-centric privacy information management system is also proposed that allows subjects to anonymously access their privacy information via their iris patterns. The system is composed of two encrypted-domain protocols: The privacy information encryption protocol encrypts the original video records using the iris pattern acquired during the subject identification phase; the privacy information retrieval protocol allows the video records to be anonymously retrieved through a GC-based iris pattern matching process. Experimental results on a public iris biometric database demonstrate the validity of our framework.

Anonymous subject identification and privacy information management in video surveillance / Luo, Ying; Cheung, Sen ching S.; Lazzeretti, Riccardo; Pignata, Tommaso; Barni, Mauro. - In: INTERNATIONAL JOURNAL OF INFORMATION SECURITY. - ISSN 1615-5262. - STAMPA. - 17:3(2018), pp. 261-278. [10.1007/s10207-017-0380-2]

Anonymous subject identification and privacy information management in video surveillance

LAZZERETTI, RICCARDO;
2018

Abstract

The widespread deployment of surveillance cameras has raised serious privacy concerns, and many privacy-enhancing schemes have been recently proposed to automatically redact images of selected individuals in the surveillance video for protection. Of equal importance are the privacy and efficiency of techniques to first, identify those individuals for privacy protection and second, provide access to original surveillance video contents for security analysis. In this paper, we propose an anonymous subject identification and privacy data management system to be used in privacy-aware video surveillance. The anonymous subject identification system uses iris patterns to identify individuals for privacy protection. Anonymity of the iris-matching process is guaranteed through the use of a garbled-circuit (GC)-based iris matching protocol. A novel GC complexity reduction scheme is proposed by simplifying the iris masking process in the protocol. A user-centric privacy information management system is also proposed that allows subjects to anonymously access their privacy information via their iris patterns. The system is composed of two encrypted-domain protocols: The privacy information encryption protocol encrypts the original video records using the iris pattern acquired during the subject identification phase; the privacy information retrieval protocol allows the video records to be anonymously retrieved through a GC-based iris pattern matching process. Experimental results on a public iris biometric database demonstrate the validity of our framework.
2018
Anonymous subject identification; Privacy information management; Privacy protection Video surveillance; Garbled circuit
01 Pubblicazione su rivista::01a Articolo in rivista
Anonymous subject identification and privacy information management in video surveillance / Luo, Ying; Cheung, Sen ching S.; Lazzeretti, Riccardo; Pignata, Tommaso; Barni, Mauro. - In: INTERNATIONAL JOURNAL OF INFORMATION SECURITY. - ISSN 1615-5262. - STAMPA. - 17:3(2018), pp. 261-278. [10.1007/s10207-017-0380-2]
File allegati a questo prodotto
File Dimensione Formato  
Luo_Preprint-Anonymous-Subject-Identification_2017.pdf

accesso aperto

Note: pre-print
Tipologia: Documento in Pre-print (manoscritto inviato all'editore, precedente alla peer review)
Licenza: Creative commons
Dimensione 1.03 MB
Formato Adobe PDF
1.03 MB Adobe PDF
Luo_Anonymous-Subject-Identification_2017.pdf

solo gestori archivio

Tipologia: Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 1.5 MB
Formato Adobe PDF
1.5 MB Adobe PDF   Contatta l'autore

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/11573/979395
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 7
  • ???jsp.display-item.citation.isi??? 6
social impact