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O-Bin: oblivious binning for encrypted data over cloud
conference contribution
posted on 2023-05-23, 11:02 authored by Ahmad, M, Pervez, Z, Byeong KangByeong Kang, Lee, SIn recent years, the data growth rate has been observed growing at a staggering rate. Considering data search as a primitive operation and to optimize this process on large volume of data, various solution have been evolved over a period of time. Other than finding the precise similarity, these algorithms aim to find the approximate similarities and arrange them into bins. Locality sensitive hashing (LSH) is one such algorithm that discovers probable similarities prior calculating the exact similarity thus enhance the overall search process in high dimensional search space. Realizing same strategy for encrypted data and that too in public cloud introduces few challenges to be resolved before probable similarity discovery. To address these issues and to formalize a similar strategy like LSH, in this paper we have formalized a technique O-Bin that is designed to work over encrypted data in cloud. By exploiting existing cryptographic primitives, O-Bin preserves the data privacy during the similarity discovery for the binning process. Our experimental evaluation for O-Bin produces results similar to LSH for encrypted data.
History
Publication title
Proceedings of the 29th International Conference on Advanced Information Networking and ApplicationsEditors
L Barolli, M Takizawa, F Xhafa, T Enokido, JH ParkPagination
352-357ISBN
9781479979042Department/School
School of Information and Communication TechnologyPublisher
IEEE-Inst Electrical Electronics Engineers IncPlace of publication
New Jersey, USAEvent title
29th International Conference on Advanced Information Networking and ApplicationsEvent Venue
Gwangju, KoreaDate of Event (Start Date)
2015-03-25Date of Event (End Date)
2015-03-27Rights statement
Copyright 2015 IEEERepository Status
- Restricted