Method of Detecting SmiShing using SVM
Jiwon Lee, Dong-Hoon Lee, In‐Suk Kim · Journal of Security Engineering · 2013
As IT technologies develop, electronic financial transactions are performed via the various devices. Financial transactions using a wireless device especially by use of a smart-phone is rapidly increasing, financial fraud using the smart-phone has become a serious social issue. Although various organizations such as investigative authority, financial institution, etc. present a lot of security measures, they have a hard time to prevent by the continuing evolution of phishing. In particular, smishing using social engineering skills is outstanding phishing technique recently. In this paper, we analyze existing detection methods and its limitations for smishing. Based on these works, we propose classification method using a machine learning algorithm focused on characteristics of message contents and sender’s address. In addition, we demonstrate that accuracy of the proposed method are better than other methods with the experimental results.