A Study on Financing Security for Smartphones Using Text Mining

With the emergence of smartphones, our lives have considerably changed. A smartphone has not only conventional calling, text-messaging, and photo-taking functions, but also performs many other functions by executing apps. In particular, more financial transactions using smartphone have recently become possible. With the global rapid rise in smartphone users and an ever-growing time and frequency of smartphone use, smartphones have become a target of malicious attacks. As a result, the damage caused by personal information leakage, phishing, and pharming has occurred more frequently. In this respect, however, very few studies have previously used crawling and text mining techniques, which have been actively studied quite recently; furthermore, network analysis has rarely been conducted. In this context, the present study collected the data from 2014 to the first half of 2016 on the trends of safe financing via smartphone with the crawling technique and analyzed the collected data with the text mining Technique. Our results suggest that there was a difference in the use of important keywords related to smartphone financial security, on the year-on-year basis. This suggests that an increasing number of financial services provided using smartphones should be accompanied by the elaboration of safe smartphone financial security services. In addition, for the sake smartphone financial security, not only manufacturers, but also banks, i.e. service providers, and users must pay specific attention to security issues.

[1]  G. P. Biswas,et al.  Secure Multi-Purpose Mobile-Banking Using Elliptic Curve Cryptography , 2016, Wirel. Pers. Commun..

[2]  Seong-Taek Park,et al.  A Study on Factors Affecting the Adoption of LTE Mobile Communication Service: The Case of South Korea , 2016, Wirel. Pers. Commun..

[3]  Tae-Gu Kang,et al.  A Case Study on Effective Technique of Distributed Data Storage for Big Data Processing in the Wireless Internet Environment , 2016, Wirel. Pers. Commun..

[4]  Eun-Mi Park,et al.  Erratum to: Factors affecting the continuous use of cloud service: focused on security risks , 2016, Cluster Computing.

[5]  Tae-Hyoung Park,et al.  A Study on Improving the Electronic Financial Fraud Prevention Service: Focusing on an Analysis of Electronic Financial Fraud Cases in 2013 , 2014, Inscrypt 2014.

[6]  Dong Hoon Lee,et al.  Outlier Detection Method for Mobile Banking with User Input Pattern and E-finance Transaction Pattern , 2014 .

[7]  Sang-Ho Lee,et al.  A Method of Enhancing Security of Internet Banking Service using Contents-Based CAPTCHA , 2013, Inscrypt 2013.

[8]  Kyoo-Sung Noh,et al.  A Study on the Authentication and Security of Financial Settlement Using the Finger Vein Technology in Wireless Internet Environment , 2016, Wirel. Pers. Commun..

[9]  Dea-Woo Park Analysis of Mobile Smishing Hacking Trends and Security Measures , 2015 .

[10]  Minho Park,et al.  OTP-Based Transaction Verification Protocol Using PUFs , 2013 .

[11]  Hong Jin,et al.  The Effects of Consumer Characteristics on Information Searching Behavior in Wireless Mobile SNS: Using SEM Analysis , 2017, Wirel. Pers. Commun..

[12]  Ki-Hong Park,et al.  Countermeasure against Social Technologic Attack using Privacy Input-Detection , 2012 .

[13]  Hwajeong Seo,et al.  Design and Implementation of Physical Secure Card for Financial Security , 2015 .

[14]  Jong-Gun Song,et al.  A new password authentication scheme using two-way password in Smartphone Banking , 2012 .

[15]  사준호,et al.  Real-time Phishing Site Detection Method , 2012 .

[16]  Mi-Hyun Ko,et al.  The effects of leadership by types of soccer instruction on big data analysis , 2016, Cluster Computing.

[17]  Do-Young Kim,et al.  A Proposal of Smart Phone App for Preventing Smishing Attack , 2015 .