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Journal Articles IEEE Transactions on Knowledge and Data Engineering Year : 2016

Privacy-Preserving Outsourced Media Search

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Abstract

This work proposes a privacy-protection framework for an important application called outsourced media search. This scenario involves a data owner, a client, and an untrusted server, where the owner outsources a search service to the server. Due to lack of trust, the privacy of the client and the owner should be protected. The framework relies on multimedia hashing and symmetric encryption. It requires involved parties to participate in a privacy-enhancing protocol. Additional processing steps are carried out by the owner and the client: (i) before outsourcing low-level media features to the server, the owner has to one-way hash them, and partially encrypt each hash-value; (ii) the client completes the similarity search by re-ranking the most similar candidates received from the server. One-way hashing and encryption add ambiguity to data and make it difficult for the server to infer contents from database items and queries, so the privacy of both the owner and the client is enforced. The proposed framework realizes trade-offs among strength of privacy enforcement, quality of search, and complexity, because the information loss can be tuned during hashing and encryption. Extensive experiments demonstrate the effectiveness and the flexibility of the framework.
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Dates and versions

hal-01391444 , version 1 (15-11-2016)

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Li Weng, Laurent Amsaleg, Teddy Furon. Privacy-Preserving Outsourced Media Search . IEEE Transactions on Knowledge and Data Engineering, 2016, 28 (10), ⟨10.1109/TKDE.2016.2587258⟩. ⟨hal-01391444⟩
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