TY  - JOUR
TI  -  Design the Framework for Detecting Malicious Mobile Web- pages in Real Time
AU  - Sushma K
AU  -  Dr. K. Thippeswamy
JO  - International Journal of Scientific Research in Computer Science, Engineering and Information Technology
PB  - Technoscience Academy
DA  - 2018/05/08
PY  - 2018
DO  - https://doi.org/10.32628/IJSRCSEIT
UR  - https://ijsrcseit.com/CSEIT184601
VL  - 4
IS  - 6
SP  - 01	
EP  - 03
AB  - Mobile specific web pages differ significantly from their desktop counterparts in content, layout and functionality. Accordingly, existing techniques to detect malicious websites are unlikely to work for such web pages. The disclosed technology includes techniques for identifying malicious mobile electronic documents, e.g. web pages or emails, based on static document features. In this paper, we design and implement kAYO, a mechanism that distinguishes between malicious and benign mobile web pages. kAYO makes this determination based on static features of a webpage ranging from the number of iframes to the presence of known fraudulent phone numbers. We then apply kAYO to a dataset of over 350,000 known benign and malicious mobile web pages and demonstrate 90% accuracy in classification. Moreover, we discover, characterize and report a number of web pages missed by Google Safe Browsing and Virus Total, but detected by kAYO.