Title of article
Graph-based KNN Algorithm for Spam SMS Detection
Author/Authors
Ho, Tran Phuc Konkuk University, Korea , Kang, Ho-Seok Konkuk University, Korea , Kim, Sung-Ryul Konkuk University, Korea
From page
2404
To page
2419
Abstract
In the modern life, SMS (Short Message Service) is one of the most necessary services on mobile devices. Because of its popularity, many companies use SMS as an effective marketing and advertising tool. Also, the popularity gives hackers chances to abuse SMS to cheat mobile users and steal personal information in their mobile phones, for example. In this paper, we propose a method to detect spam SMS on mobile devices and smart phones. Our approach is based on improving a graph-based algorithm and utilizing the KNN Algorithm - one of the simplest and most effective classification algorithms. The experimentation is carried out on SMS message collections and the results ensures the efficiency of the proposed method, with high accuracy and small processing time enough for detecting spam messages directly on mobile phones in real time.
Keywords
Spam SMS Detection , Graph , based KNN , Smartphone , Classification , Mobile security , Data mining
Journal title
Journal of J.UCS (Journal of Universal Computer Science)
Journal title
Journal of J.UCS (Journal of Universal Computer Science)
Record number
2715153
Link To Document