Privacy-Preserving Outsourced Media Search

Abstract

International audienceThis 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

Inference-Based Similarity Search in Randomized Montgomery Domains for Privacy-Preserving Biometric Identification

“…The hash values of retrieved candidates are returned to the client for refinement. The framework is extended in [29] where partial encryption is performed on the hash code of each item to prevent an untrustworthy server from precisely linking queries and database records. In particular, the server uses the unencrypted part of each item for approximate indexing and search while the client uses the encrypted part for reranking the candidates received from the server.…”

“…In our design of the three-party search protocol, we consider a model where the different parties do not necessarily trust each other. We also assume that 1) the three parities do not collude with each other, 2) the communication channel between the parties is secure (e.g., encrypted), and 3) each party may behave in a curious-but-honest way, i.e., it follows the search protocol but may use any data in possession to glean additional information [5], [6], [28], [29]. As shown in Fig.…”

Content-based multi-source encrypted image retrieval in clouds with privacy preservation

“…Many schemes have been proposed in the field of secure CBIR [12][13][14][15][16][17][18][19][20][21][22], which can be roughly classified into two categories. In the first category, image owners extract features from plain images, and then outsource both the encrypted images and the encrypted image features to the cloud.…”

Secure and Efficient Image Retrieval over Encrypted Cloud Data

“…However, the above methods are concerned more with data confidentiality than retrieval efficiency, and the cost is expensive in practical applications. In the contrary, some efficient techniques, such as order-preserving encryption (OPE) [3,4], randomized hash functions [5][6][7], and asymmetric scalar-productpreserving encryption (ASPE) [8], are widely adopted. The reason is that they take both the data confidentiality and retrieval efficiency into account.…”

“…However, the access pattern is leaked in the above schemes. To solve this issue, Weng et al [7] omit certain bits of the hash code of query image. As a result, the cloud returns all possible candidates to the user.…”