Secure JPEG scrambling enabling privacy in photo sharing

Lin, Yuan; Korshunov, Pavel; Ebrahimi, Touradj

doi:10.1109/fg.2015.7285022

Cited by 44 publications

(35 citation statements)

References 22 publications

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“…In this part, we prove that our methods hamper the gender detection like the inpainting [13], JPEG scrambling with high level [22] of protection and black box methods. Nevertheless, in the following, we conclude that the approximation using convexity preserves the human activities contrary to the others.…”

Section: Resultsmentioning

confidence: 77%

“…With several levels of security, authors in [22], pseudo-randomly invert the sign of selected transform coefficients within JPEG framework. How-ever, the tool can either protects the privacy by making the human activities not recognizable, or the contrary.…”

Section: Background and Related Workmentioning

confidence: 99%

“…In video surveillance, mostly identity but also some semantic traits are sensitive information about people. For several years, de-identification [17,18,20,22] was the major topic in privacy protection of biometrics. The goal of such privacy filters is to make the identity of people unrecognizable.…”

Section: Introductionmentioning

confidence: 99%

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De-genderization by body contours reshaping

Ruchaud

Dugelay

2017

2017 IEEE International Conference on Identity, Security and Behavior Analysis (ISBA)

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This paper deals with privacy protection in video surveillance. More specifically, the main goal of this work is to make the gender of people no more recognizable while preserving enough information concerning body shape and motion of people for action classification. We denote this processing as de-genderization. Regarding the current state-of-art methods, most of them have privacy filters only dedicated to de-identify people. These methods do not automatically imply the suppression of visual semantic traits such as gender. Therefore, we propose two approaches that modify the visual appearance of the body shape in order to de-genderize people while keeping the possibility to interpret the video. In both methods we start by extracting the contour points attached to the body shape of people in videos. Then we either mix the coordinates of the body shape and a predefined model, or we smooth the body shape by successive polygonal approximations based on convexity. Our results demonstrate that both proposed approaches protect the gender information while preserving the global body movement. The second approach based on convexity better preserves the visibility of human activities.

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Section: Resultsmentioning

confidence: 77%

Section: Background and Related Workmentioning

confidence: 99%

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De-genderization by body contours reshaping

Ruchaud

Dugelay

2017

2017 IEEE International Conference on Identity, Security and Behavior Analysis (ISBA)

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“…In our previous work, 23 we proposed a secure JPEG scrambling to ensure visual privacy in photo sharing. In such a scrambling scheme, one can scramble multiple regions of interest (ROIs) with arbitrary shapes in an image, using one or more secret keys.…”

Section: Secure Jpeg Scramblingmentioning

confidence: 99%

Privacy-preserving photo sharing based on a public key infrastructure

et al. 2015

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A significant number of pictures are posted to social media sites or exchanged through instant messaging and cloud-based sharing services. Most social media services o↵er a range of access control mechanisms to protect users privacy. As it is not in the best interest of many such services if their users restrict access to their shared pictures, most services keep users' photos unprotected which makes them available to all insiders. This paper presents an architecture for a privacy-preserving photo sharing based on an image scrambling scheme and a public key infrastructure. A secure JPEG scrambling is applied to protect regional visual information in photos. Protected images are still compatible with JPEG coding and therefore can be viewed by any one on any device. However, only those who are granted secret keys will be able to descramble the photos and view their original versions. The proposed architecture applies an attribute-based encryption along with conventional public key cryptography, to achieve secure transmission of secret keys and a fine-grained control over who may view shared photos. In addition, we demonstrate the practical feasibility of the proposed photo sharing architecture with a prototype mobile application, ProShare, which is built based on iOS platform.

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“…Yuan et al [24] proposed a privacy-preserving method based on a secure JPEG masking algorithm capable of protecting the privacy information of multiple users in an image. This method has to maintain the privacy of information in a photo sharing situation, such as social networking services.…”

Section: Related Work On Privacy-protection With Security Camerasmentioning

confidence: 99%

Hierarchical-Masked Image Filtering for Privacy-Protection

Kumaki

Fujino

2017

IEICE Trans. Inf. & Syst.

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SUMMARYThis paper presents a hierarchical-masked image filtering method for privacy-protection. Cameras are widely used for various applications, e.g., crime surveillance, environment monitoring, and marketing. However, invasion of privacy has become a serious social problem, especially regarding the use of surveillance cameras. Many surveillance cameras point at many people; thus, a large amount of our private information of our daily activities are under surveillance. However, several surveillance cameras currently on the market and related research often have a complicated or institutional masking privacy-protection functionality. To overcome this problem, a Hierarchical-Masked image Filtering (HMF) method is proposed, which has unmaskable (mask reversal) capability and is applicable to current surveillance camera systems for privacy-information protection and can satisfy privacy-protection related requirements. This method has five main features: unmasking of the original image from only the masked image and a cipher key, hierarchical-mask level control using parameters for the length of a pseudorandom number, robustness against malicious attackers, fast processing on an embedded processor, and applicability of mask operation to current surveillance camera systems. Previous studies have difficulty in providing these features. To evaluate HMF on actual equipment, an HMF-based prototype system is developed that mainly consists of a USB web camera, ultra-compact single board computer, and notebook PC. Through experiments, it is confirmed that the proposed method achieves mask level control and is robust against attacks. The increase in processing time of the HMF-based prototype system compared with a conventional non-masking system is only about 1.4%. This paper also reports on the comparison of the proposed method with conventional privacy protection methods and favorable responses of people toward the HMF-based prototype system both domestically and abroad. Therefore, the proposed HMF method can be applied to embedded systems such as those equipped with surveillance cameras for protecting privacy.

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Secure JPEG scrambling enabling privacy in photo sharing

Cited by 44 publications

References 22 publications

De-genderization by body contours reshaping

De-genderization by body contours reshaping

Privacy-preserving photo sharing based on a public key infrastructure

Hierarchical-Masked Image Filtering for Privacy-Protection

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