O-Bin: Oblivious Binning for Encrypted Data over Cloud

M. Ahmad, Z. Pervez, Kang Byeong Ho, Lee Sungyoung

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)


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.
Original languageEnglish
Title of host publicationAdvanced Information Networking and Applications (AINA), 2015 IEEE 29th International Conference on
Number of pages6
ISBN (Print)978-1-4799-7904-2
Publication statusPublished - 2015

Publication series

ISSN (Print)1550-445X


  • cloud computing
  • cryptography
  • data privacy
  • information retrieval
  • LSH
  • O-Bin
  • approximate similarities
  • cryptographic primitives
  • data growth rate
  • data search
  • encrypted data
  • high dimensional search space
  • locality sensitive hashing
  • oblivious binning process
  • probable similarity discovery
  • public cloud
  • search process
  • Encryption
  • Outsourcing
  • Servers
  • Binning
  • Cloud
  • Security and Privacy
  • Similarity discovery


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