Privacy-Preserving Content-Based Image Retrieval in the Cloud

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Storage requirements for visual data have been increasing in recent years, following the emergence of many new highly interactive multimedia services and applications for both personal and corporate use. This has been a key driving factor for the adoption of cloud-based data outsourcing solutions. However, outsourcing data storage to the Cloud also leads to new challenges that must be carefully addressed, especially regarding privacy. In this paper we propose a secure framework for outsourced privacy-preserving storage and retrieval in large image repositories. Our proposal is based on IES-CBIR, a novel Image Encryption Scheme that displays Content-Based Image Retrieval properties. Our solution enables both encrypted storage and searching using CBIR queries while preserving privacy. We have built a prototype of the proposed framework, formally analyzed and proven its security properties, and experimentally evaluated its performance and precision. Our results show that IES-CBIR is provably secure, allows more efficient operations than existing proposals, both in terms of time and space complexity, and enables more reliable practical application scenarios.

Original languageEnglish
Title of host publicationProceedings - 2015 IEEE 34th Symposium on Reliable Distributed Systems Workshops, SRDSW 2015
PublisherIEEE Computer Society
Number of pages10
ISBN (Electronic)9781467393027, 9781509000920
Publication statusPublished - 4 Jan 2016
Event34th IEEE International Symposium on Reliable Distributed Systems, SRDS 2015 - Montreal, Canada
Duration: 28 Sept 20151 Oct 2015

Publication series

NameSymposium on Reliable Distributed Systems Proceedings
PublisherIEEE Computer Society
ISSN (Print)1060-9857


Conference34th IEEE International Symposium on Reliable Distributed Systems, SRDS 2015


  • Cloud computing
  • Encryption
  • Image color analysis
  • Indexes
  • Outsourcing


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