Privacy has received much attention but is still largely ignored in the multimedia community. Consider a cloud
computing scenario, where the server is resource-abundant and is capable of finishing the designated tasks, it is
envisioned that secure media retrieval and search with privacy-preserving will be seriously treated. In view of the
fact that scale-invariant feature transform (SIFT) has been widely adopted in various fields, this paper is the first
to address the problem of secure SIFT feature extraction and representation in the encrypted domain. Since all
the operations in SIFT must be moved to the encrypted domain, we propose a homomorphic encryption-based
secure SIFT method for privacy-preserving feature extraction and representation based on Paillier cryptosystem.
In particular, homomorphic comparison is a must for SIFT feature detection but is still a challenging issue for
homomorphic encryption methods. To conquer this problem, we investigate a quantization-like secure comparison
strategy in this paper. Experimental results demonstrate that the proposed homomorphic encryption-based SIFT
performs comparably to original SIFT on image benchmarks, while preserving privacy additionally. We believe
that this work is an important step toward privacy-preserving multimedia retrieval in an environment, where
privacy is a major concern.
Media encryption technologies actively play the first line of defense in securing the access of multimedia data. Traditional cryptographic encryption can achieve provable security but is unfortunately sensitive to a single bit error, which will cause an unreliable packet to be dropped to create packet loss. In order to achieve robust
media encryption, error resilience in media encryption can be treated to be equivalent to error resilience in media transmission. This study proposes an embedded block hash searching scheme at the decoder side to achieve motion estimation and recover the lost packets, while maintaining format compliance and cryptographic provable security. It is important to note that the proposed framework is a kind of joint error-resilient video transmission/encryption and copyright protection.
The watermarking methods resistant to geometric attacks can be divided into three categories: the first category is to embed the watermark into the geometric invariant domain, the second category proposed to use template or insert periodic watermark pattern for the re-synchronization purpose, and the third category is called “feature-based watermarking scheme” in which the feature points detected in the original image are used to form local regions for both embedding and detection. However, the major weakness is their limited resistance to both extensive geometric distortions and watermark-estimation attack (WEA). In view of this, we propose a mesh-based content-dependent image watermarking method that can withstand geometric distortions and WEA. Because the first category is restricted to be affine invariant and the periodic patterns are easily removed in the second category, we have investigated to find that the third category seems to be the best choice. Our method is mainly composed of three components: (i) robust mesh generation and mesh-based embedding for resisting geometric distortions; (ii) improvement of fidelity using modified Noise Visibility Function (NVF); and (iii) construction of hash-based content-dependent watermark (CDW) for resisting WEA. Experimental results obtained from standard benchmark confirm the robustness of our method.