The crime of stealing sensitive information charges Internet customers billions of bucks a year. Refers to the techniques utilized by thieves to fish for private data in a pool of unsuspecting Internet customers. Fraudsters use fraudulent email, identity theft software to steal personal information and financial account information such as usernames and passwords. This paper discusses how to find crime hacking websites by analyzing various aspects of malicious URLs and phishing scams with machine learning techniques. We discuss the methods used to find criminal websites to steal sensitive information based on lexical features, host properties and key page layouts. We consider various machine learning algorithms to analyze features in order to better understand the structure of URLs that spread the crime of identity theft. Well-tuned parameters are useful in choosing an apt machine algorithm for classifying crime sites to steal sensitive information from the right sites. Keywords: Phishing, Machine Learning, Sensitive Data, Key Page Layouts.
₹10000 (INR)
NON IEEE -2022