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Privacy preserving content based image retrieval
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AI
DOI：10.1007/s11042-023-17168-x.png)
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摘要
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The rapid and tremendous growth of multimedia content has motivated users and organizations to upload their large scale digital content on the cloud server which makes the security of data an important issue. To overcome the problem of security in content based image retrieval (CBIR), we have proposed a novel privacy preserving image retrieval technique that efficiently retrieves similar images in an encrypted domain. Initially features of all the images in the database are extracted and then encrypted using secret key. In order to enhance the security, images are encrypted using Gauss-Square chaotic (GSC) map prior to outsourcing it to cloud server. Cloud uses modified euclidian distance (for encrypted features) to retrieve images similar to user encrypted query. Simulation results on Corel-1K and GHIM-10K illustrates that proposed technique efficiently retrieves encrypted images without compromising the retrieval accuracy. Moreover, the security analysis demonstrates the high security of proposed image encryption scheme.
Keyword:
Multimedia security
Privacy
Image retrieval
Chaotic map
期刊
IF:
3
论文数:
1.9W
被引数:
3.2W
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OAAI
OAAI分享收藏Content-based multi-source encrypted image retrieval in clouds with privacy preservation具有隐私保护的云环境下基于内容的多源加密图像检索
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