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Xun Yi , Victoria University, Melbourne
Elisa Bertino , Purdue University, West Lafayette
Jaideep Vaidya , Rutgers University, Newark
Chaoping Xing , Nanyang Technological University, Singapore
ABSTRACT
Private searching on streaming data is a process to dispatch to a public server a program, which searches streaming sources of data without revealing searching criteria and then sends back a buffer containing the findings. From an Abelian group homomorphic encryption, the searching criteria can be constructed by only simple combinations of keywords, e.g., disjunction of keywords. The recent breakthrough in fully homomorphic encryption has allowed us to construct arbitrary searching criteria theoretically. In this paper, we consider a new private query, which searches for documents from streaming data on the basis of keyword frequency, such that the frequency of a keyword is required to be higher or lower than a given threshold. This form of query can help us in finding more relevant documents. Based on the state-of-the-art fully homomorphic encryption techniques, we give disjunctive, conjunctive and complement constructions for private threshold queries based on keyword frequency. Combining the basic constructions, we further present a generic construction for arbitrary private threshold queries based on keyword frequency. Our protocols are semantically secure as long as the underlying fully homomorphic encryption scheme is semantically secure.
INDEX TERMS
binary linear code, private searching on streaming data, fully homomorphic encryption
CITATION
Xun Yi, Elisa Bertino, Jaideep Vaidya, Chaoping Xing, "Private Searching on Streaming Data Based on Keyword Frequency", IEEE Transactions on Dependable and Secure Computing, , no. 1, pp. 1, PrePrints PrePrints, doi:10.1109/TDSC.2013.36
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