Background: Our work is focused on fuzzy keyword search over encrypted data in Cloud Computing. Methods: We adapt results on private identification schemes by Bringer et al. to this new context. We here exploit a classical embedding of the edit distance into the Hamming distance. Results: Our way of doing enables some flexibility on the tolerated edit distance when looking for close keywords while preserving the confidentiality of the queries. Conclusion: Our proposal is proved secure in a security model taking into account privacy.
Relying on an asymmetric security model, Bringer et al. proposed a fuzzy search scheme based on the embedding of edit distance into Hamming distance REF .
Embedding edit distance to enable private keyword search
Human-centric Computing and Information Sciences
Human-centric Computing and Information Sciences
Computer Science