TY - JOUR
T1 - Efficient approach for mitigating mobile phishing attacks
AU - Lee, Hyungkyu
AU - Lee, Younho
AU - Seo, Changho
AU - Yoon, Hyunsoo
N1 - Publisher Copyright:
© 2018 The Institute of Electronics, Information and Communication Engineers.
PY - 2018/9
Y1 - 2018/9
N2 - We propose a method for efficiently detecting phishing attacks in mobile environments. When a user visits a website of a certain URL, the proposed method first compares the URL to a generated whitelist. If the URL is not in the whitelist, it detects if the site is a phishing site based on the results of Google search with a carefully refined URL. In addition, the phishing detection is performed only when the user provides input to the website, thereby reducing the frequency of invoking phishing detection to decrease the amount of power used. We implemented the proposed method and used 8315 phishing sites and the same number of legitimate websites for evaluating the performance of the proposed method. We achieved a phishing detection rate of 99.22%with 81.22%reduction in energy consumption as compared to existing approaches that also use search engine for phishing detection. Moreover, because the proposed method does not employ any other algorithm, software, or comparison group, the proposed method can be easily deployed.
AB - We propose a method for efficiently detecting phishing attacks in mobile environments. When a user visits a website of a certain URL, the proposed method first compares the URL to a generated whitelist. If the URL is not in the whitelist, it detects if the site is a phishing site based on the results of Google search with a carefully refined URL. In addition, the phishing detection is performed only when the user provides input to the website, thereby reducing the frequency of invoking phishing detection to decrease the amount of power used. We implemented the proposed method and used 8315 phishing sites and the same number of legitimate websites for evaluating the performance of the proposed method. We achieved a phishing detection rate of 99.22%with 81.22%reduction in energy consumption as compared to existing approaches that also use search engine for phishing detection. Moreover, because the proposed method does not employ any other algorithm, software, or comparison group, the proposed method can be easily deployed.
KW - Mobile phishing
KW - Mobile phishing detection
KW - Mobile security
KW - Phishing detection
KW - Security
UR - https://www.scopus.com/pages/publications/85053847390
U2 - 10.1587/transcom.2018EBP3020
DO - 10.1587/transcom.2018EBP3020
M3 - Article
AN - SCOPUS:85053847390
SN - 0916-8516
VL - E101B
SP - 1982
EP - 1996
JO - IEICE Transactions on Communications
JF - IEICE Transactions on Communications
IS - 9
ER -