Understanding the security and robustness of SIFT

Many content-based retrieval systems (CBIRS) describe images using the SIFT local features because of their 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. In one of their scenario, Hsu et al. in [2] show that very specific antiSIFT 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. Categories and Subject Descriptors H.3.1 [Information Storage and Retrieval]: Content Analysis and Indexing General Terms Algorithms, Security

• Type: Conference
• Year: 2010
• Where: MM
• Authors: Thanh-Toan Do, Ewa Kijak, Teddy Furon, Laurent Amsaleg
• Keywords: Images, Many Content-based Retrieval, MM 2010, Multimedia, SIFT Local Features