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O-Bin: oblivious binning for encrypted data over cloud


Ahmad, M and Pervez, Z and Kang, BH and Lee, S, O-Bin: oblivious binning for encrypted data over cloud, Proceedings of the 29th International Conference on Advanced Information Networking and Applications, 25-27 March 2015, Gwangju, Korea, pp. 352-357. ISBN 9781479979042 (2015) [Refereed Conference Paper]

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Copyright Statement

Copyright 2015 IEEE

DOI: doi:10.1109/AINA.2015.206


In 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.

Item Details

Item Type:Refereed Conference Paper
Keywords:similarity discovery, security and privacy, cloud, binning
Research Division:Information and Computing Sciences
Research Group:Cybersecurity and privacy
Research Field:Cybersecurity and privacy not elsewhere classified
Objective Division:Information and Communication Services
Objective Group:Information services
Objective Field:Electronic information storage and retrieval services
UTAS Author:Kang, BH (Professor Byeong Kang)
ID Code:107241
Year Published:2015
Web of Science® Times Cited:2
Deposited By:Information and Communication Technology
Deposited On:2016-03-08
Last Modified:2018-03-27

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