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
2 TEMICS - Digital image processing, modeling and communication

Many content-based retrieval systems (CBIRS) describe images using the SIFT local features because they provide very robust recognition capabilities. While SIFT features proved to cope with a wide spectrum of general purpose image distortions, its security has not fully been assessed yet. Hsu \emph{et al.} in~\cite{hsu09:_secur_robus_sift} 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 concerned by their analysis. This paper presents our own investigations 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.

Domains: Multimedia [cs.MM]

Thanh-Toan Do, Ewa Kijak, Teddy Furon, Laurent Amsaleg. Understanding the Security and Robustness of SIFT. [Research Report] RR-7280, INRIA. 2010. ⟨inria-00482502⟩