Security analysis of image copy detection systems based on SIFT descriptors

Content-Based Image Retrieval Systems (CBIRS) are now commonly used as a filtering mechanism against the piracy of multimedia contents. These systems often use the SIFT local-feature description scheme as its robustness against a large spectrum of image distortions has been assessed. But none of these systems have addressed the piracy problem from a ''security'' perspective. This thesis checks whether CBIRS are secure: Can pirates mount violent attacks against CBIRS by carefully studying the technology they use? First, we present the security flaws of the typical technology blocks used in state-of-the-art CBIRS. Then, we present very SIFT-specific attacks. The attacks are performed either during the keypoint detection step or during the keypoint description step. We also present a security-oriented Picture in Picture attack deluding CBIRS using post filtering geometric verifications. Experiments with a database made of 100,000 real world images confirm the effectiveness of proposed attacks.

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Source https://theses.hal.science/tel-00766932
Author Do, Thanh-Toan
Maintainer CCSD
Last Updated May 30, 2026, 06:49 (UTC)
Created May 30, 2026, 06:49 (UTC)
Identifier tel-00766932
Language en
Rights https://about.hal.science/hal-authorisation-v1/
contributor Multimedia content-based indexing (TEXMEX) ; Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA) ; Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes) ; Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes) ; Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Centre Inria de l'Université de Rennes ; Institut National de Recherche en Informatique et en Automatique (Inria)
creator Do, Thanh-Toan
date 2012-09-27T00:00:00
harvest_object_id 8912c4a1-0e6e-4c7c-a73b-78e17fe62b65
harvest_source_id 3374d638-d20b-4672-ba96-a23232d55657
harvest_source_title test moissonnage SELUNE
metadata_modified 2025-08-12T00:00:00
set_spec type:THESE