Privacy-aware searching with oblivious term matching for cloud storage

Zeeshan Pervez, Ammar Ahmad Awan, Asad Masood Khattak, Sungyoung Lee, Eui-Nam Huh

Research output: Contribution to journalArticlepeer-review

27 Citations (Scopus)


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.
Original languageEnglish
Pages (from-to)538-560
Number of pages23
JournalThe Journal of Supercomputing
Issue number2
Publication statusPublished - 2012
Externally publishedYes


  • Cloud storage
  • Data search
  • Private matching
  • Private information retrieval


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