Open AccessTop-K search scheme on encrypted data in cloud
Author(s) -
Katari Pushpa Rani,
L. Lakshmi,
Ch. Sabitha,
B. Dhana Lakshmi,
B. S. Sreeja
Publication year - 2020
Publication title -
international journal of advances in applied sciences
Language(s) - English
Resource type - Journals
eISSN - 2722-2594
pISSN - 2252-8814
DOI - 10.11591/ijaas.v9.i1.pp67-69
Subject(s) - encryption , cloud computing , computer science , tree traversal , construct (python library) , set (abstract data type) , tree (set theory) , index (typography) , scheme (mathematics) , information retrieval , computer security , data mining , algorithm , world wide web , mathematics , computer network , mathematical analysis , programming language , operating system
A Secure and Effective Multi-keyword Ranked Search Scheme on Encrypted Cloud Data. Cloud computing is providing people a very good knowledge on all the popular and relevant domains which they need in their daily life. For this, all the people who act as Data Owners must possess some knowledge on Cloud should be provided with more information so that it will help them to make the cloud maintenance and administration easy. And most important concern these days is privacy. Some sensitive data exposed in the cloud these days have security issues. So, sensitive information ought to be encrypted earlier before making the data externalized for confidentiality, which makes some keyword-based information retrieval methods outdated. But this has some other problems like the usage of this information becomes difficult and also all the ancient algorithms developed for performing search on these data are not so efficient now because of the encryption done to help data from breaches. In this project, we try to investigate the multi- keyword top-k search problem for encryption against privacy breaks and to establish an economical and secure resolution to the present drawback. we have a tendency to construct a special tree-based index structure and style a random traversal formula, which makes even identical question to supply totally different visiting ways on the index, and may additionally maintain the accuracy of queries unchanged below stronger privacy. For this purpose, we take the help of vector area models and TFIDF. The KNN set of rules are used to develop this approach.