This paper is published in Volume-4, Issue-6, 2018
Area
Computer Science
Author
A. Sarathambigai, P. Gayathiri Devi, P. Balamurugan
Org/Univ
Sengunthar Arts and Science College, Namakkal, Tamil Nadu, India
Pub. Date
12 November, 2018
Paper ID
V4I6-1158
Publisher
Keywords
Top-K model, WSN, Encryption, Big data, Associate pattern mining, WASP-Tree

Citationsacebook

IEEE
A. Sarathambigai, P. Gayathiri Devi, P. Balamurugan. Top-K associate secure pattern mining for mobile sensor data using level base utility pattern algorithm, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
A. Sarathambigai, P. Gayathiri Devi, P. Balamurugan (2018). Top-K associate secure pattern mining for mobile sensor data using level base utility pattern algorithm. International Journal of Advance Research, Ideas and Innovations in Technology, 4(6) www.IJARIIT.com.

MLA
A. Sarathambigai, P. Gayathiri Devi, P. Balamurugan. "Top-K associate secure pattern mining for mobile sensor data using level base utility pattern algorithm." International Journal of Advance Research, Ideas and Innovations in Technology 4.6 (2018). www.IJARIIT.com.

Abstract

This paper describes a secure top-k query processing scheme that is secure under the security model. The data privacy is guaranteed by encryption as well as a careful generation of data indexes. In this paper make to transform a top-k query, to a top-range query and adopt membership testing to test whether an associate pattern should be included in the query result or not. This transformation allows the storage node to find Top-k smallest or biggest data values without using numerical comparison operations, which is a key technique for the scheme to be secure under the security model. In the proposed system, it defines a new type of behavioral patterns for WSNs, termed as associated sensor patterns to capture the true correlation among sensor data. To discover such patterns, it uses to devise a highly compact tree structure, called weight associated sensor pattern tree (WASP-tree) and a mining algorithm that can efficiently discover patterns from sensor database (SD) with a single scan.