A privacy-preserving content-based image retrieval method in cloud environment

Xu, Yinghui; Gong, Jianya; Xiong, Lizhi; Wang, Chao; Wang, Jinwei; Shi, Yun-Qing

doi:10.1016/j.jvcir.2017.01.006

Cited by 65 publications

(28 citation statements)

References 34 publications

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“…CBIR is widely used in many fields such as e-commerce [32], medicine [33], military, security technology [34], multimedia digital library, Geographic information System [35], architecture and engineering design [36], intellectual property [37], crime and security prevention etc. In this paper, the effectiveness of our approach is verified in e-commerce.…”

Section: Application Simulation Analysismentioning

confidence: 99%

Content-Based Color Image Retrieval Using Block Truncation Coding Based on Binary Ant Colony Optimization

et al. 2018

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In this paper, we propose a content-based image retrieval (CBIR) approach using color and texture features extracted from block truncation coding based on binary ant colony optimization (BACOBTC). First, we present a near-optimized common bitmap scheme for BTC. Then, we convert the image to two color quantizers and a bitmap image-utilizing BACOBTC. Subsequently, the color and texture features, i.e., the color histogram feature (CHF) and the bit pattern histogram feature (BHF) are extracted to measure the similarity between a query image and the target image in the database and retrieve the desired image. The performance of the proposed approach was compared with several former image-retrieval schemes. The results were evaluated in terms of Precision-Recall and Average Retrieval Rate, and they showed that our approach outperformed the referenced approaches.

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Section: Application Simulation Analysismentioning

confidence: 99%

Content-Based Color Image Retrieval Using Block Truncation Coding Based on Binary Ant Colony Optimization

et al. 2018

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“…For privacy-preserving photo sharing on these services, three requirements need to be satisfied: 1) protection of visual information, 2) tolerance for recompression after encryption, and 3) identification of encrypted images. In terms of requirement 1, a lot of studies on secure and efficient communications have been reported [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15]. To secure multimedia data, full encryption with provable security, such as RSA and AES, is the most secure option.…”

Section: Introductionmentioning

confidence: 99%

“…To secure multimedia data, full encryption with provable security, such as RSA and AES, is the most secure option. However, most schemes do not consider requirement 2, although requirement 3 is considered in several schemes [13][14][15][16][17]. As systems that satisfy both requirements 1 and 2, Encryption-then-Compression (EtC) systems have been developed [6][7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

An Image Identification Scheme Of Encrypted Jpeg Images For Privacy-Preserving Photo Sharing Services

Iida

Kiya

2019

2019 IEEE International Conference on Image Processing (ICIP)

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We propose an image identification scheme for double-compressed encrypted JPEG images that aims to identify encrypted JPEG images that are generated from an original JPEG image. To store images without any visual sensitive information on photo sharing services, encrypted JPEG images are generated by using a block-scramblingbased encryption method that has been proposed for Encryptionthen-Compression systems with JPEG compression. In addition, feature vectors robust against JPEG compression are extracted from encrypted JPEG images. The use of the image encryption and feature vectors allows us to identify encrypted images recompressed multiple times. Moreover, the proposed scheme is designed to identify images re-encrypted with different keys. The results of a simulation show that the identification performance of the scheme is high even when images are recompressed and re-encrypted.

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“…Owing to the fact that this paper realizes similarity search, we tend to utilize global feature (such as color, shape) instead of accurate local feature (such as SIFT, BRIEF). Hence, our integrated feature is composed of widely used HSV histogram and DCT histogram [5,21,22,24]. We focus on the construction of index tree and protection of query pattern and access pattern.…”

Section: Introductionmentioning

confidence: 99%

Secure and Efficient Image Retrieval over Encrypted Cloud Data

Liang

Zhang

Cheng

et al. 2018

Security and Communication Networks

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This paper proposes a novel image retrieval scheme over encrypted cloud data, which achieves high efficiency and confidentiality. For the purpose of improving search efficiency, an index tree is often deployed in the image retrieval scheme. Meanwhile, the confidentiality of the sensitive cloud data, such as outsourced images, index tree, and query request, is also a key issue. Firstly, a balanced binary clustering algorithm is exploited over the integrated image features composed of basic features, such as HSV histogram and DCT histogram, yielding a balanced binary tree (BBT). In particular, due to the adoption of a balanced index tree, our scheme can achieve logarithmic search time. Secondly, the secure inner product is employed to encrypt the index vector and query feature. Finally, to resist the statistical attack of the frequency distribution of the retrieved results, we copy the database and merge the subtree of encrypted BBT to blind the search results. Security analysis and experimental results show that the proposed scheme is secure and efficient.

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A privacy-preserving content-based image retrieval method in cloud environment

Cited by 65 publications

References 34 publications

Content-Based Color Image Retrieval Using Block Truncation Coding Based on Binary Ant Colony Optimization

Content-Based Color Image Retrieval Using Block Truncation Coding Based on Binary Ant Colony Optimization

An Image Identification Scheme Of Encrypted Jpeg Images For Privacy-Preserving Photo Sharing Services

Secure and Efficient Image Retrieval over Encrypted Cloud Data

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