Privacy-aware searching with oblivious term matching for cloud storage

Authors:
Zeeshan Pervez;Ammar Ahmad Awan;Asad Masood Khattak;Sungyoung Lee;Eui-Nam Huh
Affiliations:
Ubiquitous Computing Lab, Department of Computer Engineering, Kyung Hee University, Yongin-si, South Korea 446-701;Ubiquitous Computing Lab, Department of Computer Engineering, Kyung Hee University, Yongin-si, South Korea 446-701;Ubiquitous Computing Lab, Department of Computer Engineering, Kyung Hee University, Yongin-si, South Korea 446-701;Ubiquitous Computing Lab, Department of Computer Engineering, Kyung Hee University, Yongin-si, South Korea 446-701;Internet Computing and Network Security Lab, Department of Computer Engineering, Kyung Hee University, Yongin-si, South Korea 446-701
Venue:
The Journal of Supercomputing
Year:
2013

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Abstract

Encryption ensures confidentiality of the data outsourced to cloud storage services. Searching the encrypted data enables subscribers of a cloud storage service to access only relevant data, by defining trapdoors or evaluating search queries on locally stored indexes. However, these approaches do not consider access privileges while executing search queries. Furthermore, these approaches restrict the searching capability of a subscriber to a limited number of trapdoors defined during data encryption. To address the issue of privacy-aware data search, we propose Oblivious Term Matching (OTM). Unlike existing systems, OTM enables authorized subscribers to define their own search queries comprising of arbitrary number of selection criterion. OTM ensures that cloud service provider obliviously evaluates encrypted search queries without learning any information about the outsourced data. Our performance analysis has demonstrated that search queries comprising of 2 to 14 distinct search criteria cost only 0.03 to 1.09 $ per 1000 requests.