Detecting Mobile Malicious Webpages in Real time
RAVI T
Assistant Professor
Department Of Information Technology Panimalar Engineering College Chennai, Tamil Nadu, India ravi_it@panimalar.ac.in
MOHIT R
Department Of Information Technology Panimalar Engineering College Chennai, Tamil Nadu, India
mohitrpani@gmail.com
NITHISH KANNA M
Department Of Information Technology Panimalar Engineering College Chennai, Tamil Nadu, India
mnithipecit01@gmail.com
MOWLESWARAN L
Department Of Information Technology Panimalar Engineering College Chennai, Tamil Nadu, India
lmowleswaran8747@gmail.com
Abstract - The mobile technology expansion and the growth of the mobile technology are two sides of a coin. A huge rush has been formed by the availability of high speed internet connections in the mobile web access of people. People now use they can do all the necessary things using their smartphones add web banking and electronic payment solutions and business communication and healthcare access. The count has been expanded by the increasing digital world of targets that are now assaulted by cybercriminals evil web pages, which they utilize in assaulting mobile device users. These pages are designed in such ways that they are able to do phishing and steal user credentials whilst they also redirect the users to non-approved destinations and distribute evil programs. The existing web security systems that employ blacklist and signature based methods are ineffective against new threats and zero-day attacks. The research study introduces a detection system that is immediate applies machine learning in mobile web page protection. Threat discovery using website behavior analysis. Its working mechanism is by ensuring 24-hour surveillance of Webpage layouts and webpage running URL properties system data in order to have better identification of websites results. The technique provides rapid detection outcomes along with low computing needs which protect mobile phones with an efficient. security system.
The keywords include Mobile Security, Malicious Webpages, etc. Phishing Attack, Live Attack Detection, Machine Web Threat Analysis, Learning.
