Paper Info
Title
Feature Based Approach for Detection of Smishing Messages in the Mobile Environment
Abstract
AbstractSmishing is a security attack that is performed by sending a fake message intending to steal personal credentials of mobile users. Nowadays, smishing attack becomes popular due to the massive growth of mobile users. The smishing message is very harmful since its target to financial benefits. In this article, the authors present a new feature-based approach to detect smishing messages in the mobile environment. This approach offers ten novel features that distinguish the fake messages from the ham messages. In this article, the authors have also identified the nineteen most suspicious keywords, which are used by the attacker to lure victims. This article has implemented these features on benchmarked dataset and applied numerous classification algorithms to judge the performance of the proposed approach. Experimental outcomes indicate that proposed approach can detect smishing messages with the 94.20% true positive rate and 98.74% overall accuracy. Furthermore, the proposed approach is very efficient for the detection of the zero hour attack.
Year
DOI
Venue
2019
10.4018/JITR.2019040102
Periodicals
Keywords
Field
DocType
Smishing, Machine Learning, Mobile Computing, Short Message Services
Data mining,Computer science,Feature based
Journal
Volume
Issue
ISSN
12
2
1938-7857
Citations 
PageRank 
References 
2
0.47
16
Authors
2
Name
Order
Citations
PageRank
Ankit Kumar Jain1817.77
Brij B. Gupta2416.02