Towards Privacy-Preserving Content-Based Image Retrieval in Cloud Computing

Xia, Zhihua; Zhu, Yi; Sun, Xingming; Qin, Zhan; Ren, Kui

doi:10.1109/tcc.2015.2491933

Cited by 160 publications

(79 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The inverted file identifier vectors are encrypted by an additive homomorphic encryption or pseudo-random position permutations. In [108], a privacy-preserving content-based image retrieval (CBIR) scheme is proposed to allow the data owner outsource the image database and CBIR operation to the cloud server without disclosing its actual content. The proposed scheme let the cloud server can solve earth movers distance as a linear programming problem without sensitive information of the searched image.…”

Section: Generating Cipher-images In Other Application Scenariosmentioning

confidence: 99%

When an attacker meets a cipher-image in 2018: A year in review

Zhang

Xie

2019

Journal of Information Security and Applications

148

121

View full text Add to dashboard Cite

This paper aims to review the encountered technical contradictions when an attacker meets the cipher-images encrypted by the image encryption schemes (algorithms) proposed in 2018 from the viewpoint of an image cryptanalyst. The most representative works among them are selected and classified according to their essential structures. Almost all image cryptanalysis works published in 2018 are surveyed due to their small number. The challenging problems on design and analysis of image encryption schemes are summarized to receive the attentions of both designers and attackers (cryptanalysts) of image encryption schemes, which may promote solving scenario-oriented image security problems with new technologies.

show abstract

Section: Generating Cipher-images In Other Application Scenariosmentioning

confidence: 99%

When an attacker meets a cipher-image in 2018: A year in review

Zhang

Xie

2019

Journal of Information Security and Applications

148

121

View full text Add to dashboard Cite

show abstract

“…The homomorphic encryption results in high computational complexity that makes it consume too much time. Xia et al [14] proposed a secure CBIR scheme with Bag-of-Words model and Earth Movers Distance. The retrieval index was constructed by locality-sensitive hashing.…”

Section: Related Workmentioning

confidence: 99%

“…Many schemes have been proposed in the field of secure CBIR [12][13][14][15][16][17][18][19][20][21][22], which can be roughly classified into two categories. In the first category, image owners extract features from plain images, and then outsource both the encrypted images and the encrypted image features to the cloud.…”

Section: Introductionmentioning

confidence: 99%

Content-based multi-source encrypted image retrieval in clouds with privacy preservation

Shen

Cheng

Zhu

et al. 2020

Future Generation Computer Systems

View full text Add to dashboard Cite

Content-based image retrieval (CBIR) is one of the fundamental image retrieval primitives. Its applications can be found in various areas, such as art collections and medical diagnoses. With an increasing prevalence of cloud computing paradigm, image owners desire to outsource their images to cloud servers. In order to deal with the risk of privacy leakage of images, images are typically encrypted before they are outsourced to the cloud, which makes CBIR an extremely challenging task. Existing studies focus on the scenario with only a single image owner, leaving the problem of CBIR with multiple image sources (i.e., owners) unaddressed.In this paper, we propose a secure CBIR scheme that supports Multiple Image owners with Privacy Protection (MIPP). We encrypt image features with a secure multi-party computation technique, which allows image owners to encrypt image features with their own keys. This enables efficient image retrieval over images gathered from multiple sources, while guaranteeing that image privacy of an individual image owner will not be leaked to other image owners. We also propose a new method for similarity measurement of images that can avoid revealing image similarity information to the cloud. Theoretical analysis and experimental results demonstrate that MIPP achieves retrieval accuracy and efficiency simultaneously, while preserving image privacy.

show abstract

“…The results show that the algorithm based on homomorphic encryption is time-consuming despite its high level of security. Xia et al [17] proposed an image retrieval scheme based on the scale-invariance feature transform (SIFT) feature and the earth mover's distance (EMD). This scheme uses the SIFT algorithm to extract the image feature.…”

Section: Related Workmentioning

confidence: 99%

A Content-Based Image Retrieval Scheme Using an Encrypted Difference Histogram in Cloud Computing

et al. 2017

Self Cite

View full text Add to dashboard Cite

Content-based image retrieval (CBIR) has been widely used in many applications. Large storage and computation overheads have made the outsourcing of CBIR services attractive. However, the privacy issues brought by outsourcing have become a big problem. In this paper, a secure CBIR scheme based on an encrypted difference histogram (EDH-CBIR) is proposed. Firstly, the image owner calculates the order or disorder difference matrices of RGB components and encrypts them by value replacement and position scrambling. The encrypted images are then uploaded to the cloud server who extracts encrypted difference histograms as image feature vectors. To search similar images, the query image is encrypted by the image users as the image owner does, and the query feature vector is extracted by the cloud server. The Euclidean distance between query feature vector and image feature vector is calculated to measure the similarity. The security analysis and experiments demonstrate the usability of the proposed scheme.

show abstract

Towards Privacy-Preserving Content-Based Image Retrieval in Cloud Computing

Cited by 160 publications

References 32 publications

When an attacker meets a cipher-image in 2018: A year in review

When an attacker meets a cipher-image in 2018: A year in review

Content-based multi-source encrypted image retrieval in clouds with privacy preservation

A Content-Based Image Retrieval Scheme Using an Encrypted Difference Histogram in Cloud Computing

Contact Info

Product

Resources

About