Deluding image recognition in sift-based cbir systems

MiFor '10 Pub Date : 2010-10-29 DOI:10.1145/1877972.1877977
Thanh-Toan Do, Ewa Kijak, T. Furon, L. Amsaleg
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引用次数: 43

Abstract

Content-Based Image Retrieval Systems used in forensics related contexts require very good image recognition capabilities. Therefore they often use the SIFT local-feature description scheme as its robustness against a large spectrum of image distortions has been assessed. In contrast, the security of SIFT is still largely unexplored. We show in this paper that it is possible to conceal images from the SIFT-based recognition process by designing very SIFT-specific attacks. The attacks that are successful in deluding the system remove keypoints and simultaneously forge new keypoints in the images to be concealed. This paper details several strategies enforcing image concealment. A copy-detection oriented experimental study using a database of 100,000 real images together with a state-of-art image search system shows these strategies are effective. This is a very serious threat against systems, endangering forensics investigations.
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基于筛选的模糊图像识别系统
基于内容的图像检索系统在法医相关环境中使用,需要非常好的图像识别能力。因此,他们经常使用SIFT局部特征描述方案,因为它对大范围图像失真的鲁棒性已经被评估。相比之下,SIFT的安全性在很大程度上仍未得到探索。我们在本文中表明,通过设计非常特定于sift的攻击,可以从基于sift的识别过程中隐藏图像。成功欺骗系统的攻击会移除关键点,同时在要隐藏的图像中伪造新的关键点。本文详细介绍了实施图像隐藏的几种策略。一项针对复制检测的实验研究使用了100,000张真实图像的数据库以及最先进的图像搜索系统,结果表明这些策略是有效的。这是对系统的严重威胁,危及取证调查。
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