We also conduct an experimental analysis to demonstrate the applicability of the proposed scheme in practical cloud systems.īoneh, D., Di Crescenzo, G., Ostrovsky, R., & Persiano, G. We rigorously prove the proposed schemes are adaptively semantic secure. The proposed similarity search schemes can guarantee asymptotically optimal performance for multi-user settings. Specifically, the proposed schemes enable flexible similarity searches over encrypted data even when the given data have different format, encoding, or editing. In this paper, we propose efficient multi-user similarity search schemes for cloud storage. However, previous similarity search schemes supporting multi-user settings incur unreasonable communication costs between the users and data owners during the search. ![]() ![]() Similarity search over encrypted data provides decryptionless similarity testing between data and search queries which are encrypted by the data owner and users, respectively. ![]() Thus, data are uploaded in encrypted form in many cloud applications while providing some basic yet critical functionalities, such as the ability to search. In cloud-assisted data outsourcing systems, the privacy of sensitive data is a major concern.
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