Privacy Preserving Search over Encrypted Data on Cloud |
Author(s): |
Kedar Jangam , JSPM Rajarshi Shahu College of Engineering Tathawade, Pune; Ajinkya Ingle, JSPM Rajarshi Shahu College of Engineering Tathawade, Pune; Rajendra Hiray, JSPM Rajarshi Shahu College of Engineering Tathawade, Pune; Ravina Dhage, JSPM Rajarshi Shahu College of Engineering Tathawade, Pune; Prof. R. T. Umbare, JSPM Rajarshi Shahu College of Engineering Tathawade, Pune |
Keywords: |
Cloud Data Sharing, CP-ABE, Key Management, Security, Efficiency |
Abstract |
Cloud computing provides people and enterprises Brobdingnagian computing power and ascendable storage capacities to support a range of huge data applications in domains like health care and scientiï¬c analysis, thus additional and additional knowledge homeowners square measure concerned to to source their knowledge on cloud servers for excellent convenience in knowledge management and mining. However, knowledge sets like health records in electronic documents typically contain sensitive data that brings regarding privacy problems if the documents square measure free shared to partially untrusted third-parties in cloud. A sensible and wide used technique for knowledge privacy preservation is to encrypt data before outsourcing to the cloud servers, that but reduces knowledge utility and makes many ancient knowledge analytic operators like keyword-based top-k document retrieval obsolete. During this paper, we tend to investigate the multi-keyword top-k search problem for massive encryption against privacy breaches, associated arrange to determine an efï¬cient and secure answer to the current drawback. Speciï¬cally, for the privacy concern of question knowledge, we tend to construct a special tree-based index structure and style a random traversal formula, which makes even a similar question to provide totally different visiting ways on the index, and would possibly to boot maintain the accuracy of queries unchanged under stronger privacy. For up the question efï¬ciency, we tend to tend to propose a gaggle multi-keyword top-k search theme supported plan of partition wherever a gaggle of tree-based indexes square measure made for all documents. Finally, we tend to mix these ways along into an efï¬cient and secure approach to deal with our projected top k similarity search. In-depth experimental results on real-life knowledge sets demonstrate that our projected approach will signiï¬cantly improve the potential of defensive the privacy breaches, the measurability and the time efï¬ciency of question process over the progressive ways. |
Other Details |
Paper ID: IJSRDV5I90452 Published in: Volume : 5, Issue : 9 Publication Date: 01/12/2017 Page(s): 1071-1073 |
Article Preview |
|
|