Identification of Phishing Urls Using Machine Learning

LEARNING TO DETECT PHISHING URLs

Phishing attacks have been on the rise and performing certain actions such as mouse hovering, clicking, etc. on malicious URLs may cause unsuspecting Internet users to fall victims of identity theft or other scams. In this paper, we study the anatomy of phishing URLs that are created with the specific intent of impersonating a trusted third party to trick users into divulging personal data. Unl...

Lightweight Phishing URLs Detection Using N-gram Features

Phishing is a kind of attack that belongs to social engineering and this attack seeks to trick people in order to let them reveal their confidential information. Several methods are introduced to detect phishing websites by using different types of features. Unfortunately, these techniques implemented for specific attack vector such as detecting phishing emails which make implementing wide scop...

Feature-based Malicious URL and Attack Type Detection Using Multi-class Classification

Nowadays, malicious URLs are the common threat to the businesses, social networks, net-banking etc. Existing approaches have focused on binary detection i.e. either the URL is malicious or benign. Very few literature is found which focused on the detection of malicious URLs and their attack types. Hence, it becomes necessary to know the attack type and adopt an effective countermeasure. This pa...

A Review on Phishing URL Detection using Machine Learning Systems

Seeking sensitive user data in the form of online banking user-id and passwords or credit card information, which may then be used by ‘phishers’ for their own personal gain is the primary objective of the phishing e-mails. With the increase in the online trading activities, there has been a phenomenal increase in the phishing scams which have now started achieving monstrous proportions. This pa...

Detection of Phishing Attacks: A Machine Learning Approach