A Novel Feature Matching Ranked Search Mechanism Over Encrypted Cloud Data
A Novel Feature Matching Ranked Search Mechanism Over Encrypted Cloud Data
IEEE BASE PAPER ABSTRACT:
Encrypted search technology has been studied extensively in recent years. With more and more information being stored in cloud, creating indexes with independent keywords has resulted in enormous storage cost and low search accuracy, which has become an urgent problem to be solved. Thus, in this paper, we propose a new feature matching ranked search mechanism (FMRSM) for encrypted cloud data. This mechanism uses feature score algorithm (FSA) to create indexes, which allows multi-keywords which are extracted from a document as a feature to be mapped to one dimension of the index. Thus, the storage cost of indexes can be reduced and the efficiency of encryption can be improved. Moreover, FMRSM uses a matching score algorithm (MSA) in generating trapdoor process. With the help of FSA, the matching score algorithm can rank the search results according to the type of match and the number of matching keywords, and therefore it is able to return results with higher ranking accuracy. Comprehensive analysis prove that our mechanism is more feasible and effective.
PROJECT OUTPUT VIDEO:
SYSTEM REQUIREMENTS:
HARDWARE REQUIREMENTS:
- System : Pentium i3 Processor
- Hard Disk : 500 GB.
- Monitor : 15’’ LED
- Input Devices : Keyboard, Mouse
- Ram : 2 GB
SOFTWARE REQUIREMENTS:
- Operating System : Windows 10 / 11.
- Coding Language : JAVA.
- Frontend : JSP, HTML, CSS, JavaScript.
- IDE Tool : NetBeans IDE 8.2.
- Database : MYSQL.
REFERENCE:
LIANGGUI LIU AND QIUXIA CHEN, “A Novel Feature Matching Ranked Search Mechanism Over Encrypted Cloud Data”, IEEE 2020.
