Open AccessStudy of Dynamic Multikeyword Text Search Techniques over Encrypted Data in Cloud
Author(s) -
Ankita Puri,
Naveen Kumari
Publication year - 2017
Publication title -
international journal of advanced research in computer science and software engineering
Language(s) - English
Resource type - Journals
eISSN - 2277-6451
pISSN - 2277-128X
DOI - 10.23956/ijarcsse/v7i7/0110
Subject(s) - cloud computing , computer science , outsourcing , encryption , overhead (engineering) , information retrieval , similarity (geometry) , matching (statistics) , set (abstract data type) , service (business) , database , data mining , computer security , artificial intelligence , statistics , mathematics , economy , political science , law , economics , image (mathematics) , programming language , operating system
Day by Day ,with the advancement of modern technology over cloud computing motivating the data owners to outsource their data to the cloud server like Amazon, Microsoft, Azure etc .With the help of data outsourcing ,the organization can provide reliable data services to their user without any management of the overhead concern. Suppose, a large number of users that are on cloud and large number of documents on cloud, Its important for the service provider to allow multi-keyword query and provided the result that meet efficient data retrieval needs. In this paper, for the first time, we define and solve the challenging problem of privacy preserving multi-keyword ranked search over encrypted cloud data (MRSE), and establish a set of strict privacy requirements for such a secure cloud data utilization system to become a reality. Among various multi-keyword semantics, we choose the efficient principle of “coordinate matching”, i.e., as many matches as possible, to capture the similarity between search query and data documents, and further use “inner product similarity” to quantitatively formalize such principle for similarity measurement.