Privacy-Privacy-Preserving Multikeyword Similarity Search Over Outsourced Cloud Data
Abstract— Privacy-Preserving Multikeyword Similarity Search Over Outsourced Cloud Data. The amount of data generated by individuals and enterprises is rapidly increasing. With the < Final Year Projects 2016 > emerging cloud comput-ing paradigm, the data and corresponding complex management tasks can be outsourced to the cloud for the management flexibility and cost savings. Unfortunately, as the data could be sensitive, the direct data outsourcing would have the problem of privacy leakage. The encryption can be used, before the data outsourcing, with the concern that the operations can still be accomplished by the cloud.We consider the multi keyword similarity search over outsourced cloud data. In particular, with the consideration of the text data only, multiple keywords are speciﬁed by the user. The cloud returns the ﬁles containing more than a threshold number of input keywords or similar keywords, where the similarity here is deﬁned according to the edit distance metric. We propose three solutions, where blind signature provides the user access privacy, and a novel use of Bloom ﬁlter’s bit pattern provides the speedup of search task at the cloud side. Our ﬁnal design to achieve the search is secure against insider threats and efﬁcient in terms of the search time at the cloud side. Performance evaluation and analysis are used to demonstrate the practicality of our proposed solutions.
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