Privacy-protected Image Research Articles

Image Steganography-based Copyright and Privacy-Protected Image Trading Systems

This paper proposes steganography-based copyright- and privacy-protected image trading systems using image transformation, i.e., either discrete cosine transform (DCT) or Hadamard transform (HT). In the systems, there are a content provider (CP), a consumer, the first trusted third party (TTP), and the second TTP. To protect the copyright of the image, the consumer ID is embedded into the amplitude components of the commercial image by the first TTP using the digital fingerprinting technique, and to protect the consumer's privacy against the first TTP and a malicious third party (s), the image steganography is applied to the commercial image by using image transformation. A color dummy image is used instead of a gray dummy image for security purposes. After applying the image transformation to both images, the coefficient signs of the commercial image are replaced by the coefficient signs of the dummy image pixel-by-pixel so that the inversely transformed commercial image looks like the dummy image instead of the commercial image. Once the consumer receives the fingerprinted image from the first TTP and the coefficient signs of the commercial image from the second TTP, the consumer reconstructs the fingerprinted commercial image without losing the hidden fingerprint at all because of the compatibility of the proposed image steganography method and the amplitude-based fingerprinting method. The experimental results confirm that the stego-images generated by the proposed systems do not look suspicious with higher qualities compared with those generated by existing systems. Moreover, the fingerprinted image quality and the correct fingerprint extracting rate have been improved by the proposed systems.

Heterogeneous and Customized Cost-Efficient Reversible Image Degradation for Green IoT

With the large-scale deployment of the Internet of Things (IoT) in daily life, more and more privacy data are collected by IoT devices. These data are not directly physically controlled by users, which may cause privacy concerns. In fact, privacy has become one of the significant problems faced by IoT. In this article, we mainly study the protection of image privacy under the green IoT. We have conducted an in-depth analysis of the green IoT scenario and put forward the scope and corresponding goals that the scheme should have. Motivated by this, a novel image privacy protection scheme is proposed, i.e., heterogeneous and customized cost-efficient reversible image degradation for green IoT. This scheme fully considers the characteristics of privacy and the various users’ diverse requirements to achieve a heterogeneous and customized privacy protection. Meanwhile, cost effectiveness cannot be confined to the efficiency of the direct image processing at the expense of greatly increasing costs in other aspects, such as transmission and reversion. It is mitigated by preserving some visual content in the privacy-protected image. It also improves the image compression efficiency and ensures that the user can select the desired image according to the visual content for reversion. Some experiments have been carried out to demonstrate that this work has achieved the proposed scope and corresponding goals.

A New Copyright- and Privacy-Protected Image Trading System Using a Novel SteganographyBased Visual Encryption Scheme

In copyright- and privacy-protected image trading systems, the image sent to the trusted third party (TTP) is visually encrypted, and the image is traditionally unrecognizable. The image, however, is suspicious and has possibility to be attacked. Image steganography then becomes more interesting than image encryption for this application, however, applying image steganography instead of image encryption degrades the fingerprint extraction performance. In addition, the CP is allowed to directly contact with the consumer in the conventional systems. Thus, the consumer’s privacy is not protected completely. This paper then proposes a new copyright- and privacy-protected image trading system with a novel steganography-based visual encryption scheme, where the scheme protects a commercial image much more securely by generating a recognizable image instead of a suspicious encrypted image. By replacing amplitude components of a dummy image by those of a commercial image, the output image looks like a degraded dummy image instead of the commercial image, while it contains some details of the commercial image, i.e., the amplitude components of the commercial image are hidden into a dummy cover image. A discrete cosine transform-based fingerprinting method, which is compatible with the proposed amplitude component replacing scheme, is also proposed in this paper to solve the problem of applying image steganography. As another contribution of this paper, the CP is not allowed to directly send the image reconstruction key to the consumer, for further consumer’s privacy protection. The second TTP is then introduced to the proposed system, and in addition, the image reconstruction key is encrypted by the CP before being sent to the consumer via the second TTP for more security. Experimental results show that the proposed scheme generates recognizable images and perfectly visually encrypts the commercial images. It also achieves much higher reconstructed image qualities than those of the conventional scheme, and the proposed system simultaneously enhances the fingerprinting performance using the proposed compatible fingerprinting method.

Effective evaluation of privacy protection techniques in visible and thermal imagery

Privacy protection may be defined as replacing the original content in an image region with a (less intrusive) content having modified target appearance information to make it less recognizable by applying a privacy protection technique. Indeed, the development of privacy protection techniques also needs to be complemented with an established objective evaluation method to facilitate their assessment and comparison. Generally, existing evaluation methods rely on the use of subjective judgments or assume a specific target type in image data and use target detection and recognition accuracies to assess privacy protection. An annotation-free evaluation method that is neither subjective nor assumes a specific target type is proposed. It assesses two key aspects of privacy protection: “protection” and “utility.” Protection is quantified as an appearance similarity, and utility is measured as a structural similarity between original and privacy-protected image regions. We performed an extensive experimentation using six challenging datasets (having 12 video sequences), including a new dataset (having six sequences) that contains visible and thermal imagery. The new dataset is made available online for the community. We demonstrate effectiveness of the proposed method by evaluating six image-based privacy protection techniques and also show comparisons of the proposed method over existing methods.

Residual enhanced visual vector as a compact signature for mobile visual search

Many mobile visual search (MVS) systems transmit query data from a mobile device to a remote server and search a database hosted on the server. In this paper, we present a new architecture for searching a large database directly on a mobile device, which can provide numerous benefits for network-independent, low-latency, and privacy-protected image retrieval. A key challenge for on-device retrieval is storing a large database in the limited RAM of a mobile device. To address this challenge, we develop a new compact, discriminative image signature called the Residual Enhanced Visual Vector (REVV) that is optimized for sets of local features which are fast to extract on mobile devices. REVV outperforms existing compact database constructions in the MVS setting and attains similar retrieval accuracy in large-scale retrieval as a Vocabulary Tree that uses 25× more memory. We have utilized REVV to design and construct a mobile augmented reality system for accurate, large-scale landmark recognition. Fast on-device search with REVV enables our system to achieve latencies around 1s per query regardless of external network conditions. The compactness of REVV allows it to also function well as a low-bitrate signature that can be transmitted to or from a remote server for an efficient expansion of the local database search when required.

Recoverable Privacy Protection for Video Content Distribution

This paper presents a method which attains recoverable privacy protection for video content distribution. The method is based on discrete wavelet transform (DWT), which generates scaling coefficients and wavelet coefficients. In our method, scaling coefficients, which can be regarded as a low-resolution image of an original image, are used for producing privacy-protected image. On the other hand, wavelet coefficients, which can be regarded as privacy information, are embedded into the privacy-protected image via information hiding technique. Therefore, privacy protected image can be recovered by authorized viewers if necessary. The proposed method is fully analyzed through experiments from the viewpoints of the amount of the embedded privacy information, the deterioration due to the embedding, and the computational time.

One-Time Key Based Phase Scrambling for Phase-Only Correlation between Visually Protected Images

One-time key based phase scrambling is proposed for privacy-protected image matching. The image matching is performed using invisible templates that are protected by phase scrambling. A key for phase scrambling is not required for the image matching, and the key can even be discarded after scrambling if the template does not need to be reconstructed. Theoretical analyses are presented to provide guidelines for designing key parameters that affect the visual effect and image matching. Experimental results demonstrate the effectiveness and appropriateness of the proposed method.