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This package can search encrypted data allowing fuzzy matching.
It allows searching data on encrypted files using fuzzy search to allow users to search for text that may not be exact but it is similar.
The package provides Web application that allows users to send the files that need to be searched by the users with keywords that they provide.
|Searching for text in a data streams is a function that many application needs to allow their users to perform when they want to search for the data that they are looking for.
However, users often misspell the words that they specify when they are prompted to enter what they are searching for.
Fuzzy search is a method for searching that allows a certain tolerance for user misspelling mistakes.
This package provides a solution that can perform fuzzy search on encrypted data files.
Fuzzy Keyword Search on Encrypted Data
Fuzzy Keyword Search on Encrypted Data is not very common because of engineering and mathematical challenge it posses to system, Security is very important in modern data oriented world and with great security we have compromised the usability of searching with fuzzy keywords. This project uses the reasearch that has been done on this topic and implements it to demonstrate how we take security and privacy in parallel with usability and ofcourse without compromising security.
As Cloud Computing becomes prevalent, more and more sensitive information are being centralized into the cloud. Although traditional searchable encryption schemes allow a user to securely search over encrypted data through keywords and selectively retrieve files of interest, these techniques support only exact keyword search. In this paper, for the first time we formalize and solve the problem of effective fuzzy keyword search over encrypted cloud data while maintaining keyword privacy.
Fuzzy keyword search greatly enhances system usability by returning the matching files when users? searching inputs exactly match the predefined keywords or the closest possible matching files based on keyword similarity semantics, when exact match fails. In our solution, we exploit edit distance to quantify keywords similarity and develop two advanced techniques on constructing fuzzy keyword sets, which achieve optimized storage and representation overheads. We further propose a brand new symbol-based trie-traverse searching scheme, where a multi-way tree structure is built up using symbols transformed from the resulted fuzzy keyword sets.
Through rigorous security analysis, we show that our proposed solution is secure and privacypreserving, while correctly realizing the goal of fuzzy keyword search. Extensive experimental results demonstrate the efficiency of the proposed solution.
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