Understanding the Security and Robustness of SIFT

Thanh-Toan Do 1 Ewa Kijak 1 Teddy Furon 2 Laurent Amsaleg 1
1 TEXMEX - Multimedia content-based indexing
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, Inria Rennes – Bretagne Atlantique
2 TEMICS - Digital image processing, modeling and communication
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, Inria Rennes – Bretagne Atlantique
Abstract : Many content-based retrieval systems (CBIRS) describe im- ages using the SIFT local features because of their very ro- bust recognition capabilities. While SIFT features proved to cope with a wide spectrum of general purpose image distor- tions, its security has not fully been assessed yet. In one of their scenario, Hsu et al. in [2] show that very specific anti- SIFT attacks can jeopardize the keypoint detection. These attacks can delude systems using SIFT targeting application such as image authentication and (pirated) copy detection. Having some expertise in CBIRS, we were extremely con- cerned by their analysis. This paper presents our own inves- tigations on the impact of these anti-SIFT attacks on a real CBIRS indexing a large collection of images. The attacks are indeed not able to break the system. A detailed analysis explains this assessment.
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Communication dans un congrès
ACM. ACM Multimedia, Oct 2010, Firenze, Italy. 2010
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Thanh-Toan Do, Ewa Kijak, Teddy Furon, Laurent Amsaleg. Understanding the Security and Robustness of SIFT. ACM. ACM Multimedia, Oct 2010, Firenze, Italy. 2010. 〈inria-00505843〉

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