Practical Privacy-Preserving Content-Based Retrieval in Cloud Image Repositories

Ferreira, Bernardo; Rodrigues, João; Leitão, João; Domingos, Henrique

doi:10.1109/tcc.2017.2669999

Cited by 86 publications

(44 citation statements)

References 32 publications

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“…The framework works on both encrypted storage and searching using Content-Based Image Retrieval queries while preserving privacy against honest-but-curious cloud administrators. This system not work on colour and texture features for image retrieval [8]. This work is the first to target the importance of privacy-preserving SIFT (PPSIFT) and to address the problem of secure SIFT feature extraction and representation in the encrypted domain.…”

Section: Related Workmentioning

confidence: 99%

Survey on Secure and Efficient Content-Based Retrieval in Cloud Image Repositories

S¹

2020

IJRASET

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Many cloud stages ascend to meet sincere prerequisites for broad volume of individual picture store, sharing and search. Truth be told the vast majority of those pictures contain delicate secure information (e.g., Human, territory and any event) and people's insurance concerns ruin their venture into untrusted administrations, the present cloud stages give little help to picture security confirmation that is security assurance. Confronting extensive scale images from numerous clients i.e. user's, it is extremely challenging for the cloud to keep up the record structure and schedule parallel calculation without learning up anything about the image contents and indices. In this work, present a novel that is Privacy-protecting Content based Image Search framework on Cloud, or, in other words towards possible cloud services which give secure content based extensive scale image search with fine-grained access control using Shape-Based Invariant Texture Index (SITI). Users can search on others' images on the off chance that they are approved by the image owners. Larger part of the computationally serious part is handled by the cloud, and a querier can now simply send the query and get the search outcome. Specially, to manage enormous images, will designed our framework suitable for distributed and parallel calculation and introduce several optimizations with further facilitate the search procedure. Our security examination and model system assessment results will exhibit that this work adequately verifies the picture assurance expecting practically no exertion of computation and correspondence.

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Section: Related Workmentioning

confidence: 99%

Survey on Secure and Efficient Content-Based Retrieval in Cloud Image Repositories

S¹

2020

IJRASET

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“…However, the extracted features cannot be used for image similarity retrieval. Ferreira et al [22] proposed an secure image encryption algorithm for image retrieval, and separately processed the image color information and texture information. This scheme encrypted texture information by random encryption algorithm, and protected color information by using deterministic encryption.…”

Section: Related Workmentioning

confidence: 99%

“…However, the color histogram ignores the texture information of the image. Inspired by [22], a new image retrieval scheme based on a difference histogram is proposed to improve the retrieval accuracy.…”

Section: Related Workmentioning

confidence: 99%

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

et al. 2017

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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.

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“…In ciphertext domain research, many schemes are proposed to protect data privacy. Ferreira et al [2] proposed the practical content-based image retrieval (CBIR) scheme in an image repository. Xia et al [3] proposed an efficient CBIR scheme in cloud computing.…”

Section: Introductionmentioning

confidence: 99%

A Privacy-Protected Image Retrieval Scheme for Fast and Secure Image Search

Wang

Cheng

et al. 2020

Symmetry

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With the development of multimedia technology, the secure image retrieval scheme has become a hot research topic. However, how to further improve algorithm performance in the ciphertext needs to be further explored. In this paper, we propose a secure image retrieval scheme based on a deep hash algorithm for index encryption and an improved 4-Dimensional(4-D)hyperchaotic system. The main contributions of this paper are as follows: (1) A novel secure retrieval scheme is proposed to control data transmission. (2) An improved 4-D hyperchaotic system is proposed to preserve privacy. (3) We propose an improved deep pairwise-supervised hashing (DPSH) algorithm and secure kNN to perform index encryption and propose an improved loss function to train the network model. (4) A secure access control scheme is shown, which aims to achieve secure access for users. The experimental results show that the proposed scheme has better retrieval efficiency and better security.

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Practical Privacy-Preserving Content-Based Retrieval in Cloud Image Repositories

Cited by 86 publications

References 32 publications

Survey on Secure and Efficient Content-Based Retrieval in Cloud Image Repositories

Survey on Secure and Efficient Content-Based Retrieval in Cloud Image Repositories

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

A Privacy-Protected Image Retrieval Scheme for Fast and Secure Image Search

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