Reliability and Robustness analysis of Machine Learning based Phishing URL Detectors

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...

Malicious URL Detection using Machine Learning: A Survey

Malicious URL, a.k.a. malicious website, is a common and serious threat to cybersecurity. Malicious URLs host unsolicited content (spam, phishing, drive-by exploits, etc.) and lure unsuspecting users to become victims of scams (monetary loss, theft of private information, and malware installation), and cause losses of billions of dollars every year. It is imperative to detect and act on such th...

Security Evaluation of Pattern Classifier against Phishing URL Detection

— Pattern classification is a branch of machine learning that focuses on recognition of patterns and regularities in data. In adversarial applications like biometric authentication, spam filtering, network intrusion detection the pattern classification systems are used. Extending pattern classification theory and design methods to adversarial environment is thus a novel and very relevant resear...

Detection of Phishing Attacks: A Machine Learning Approach

Concept Reliability in Machine Learning

Much machine learning research addresses inductive learning — learning relationships from a set of examples (Michalski (1986) provides an excellent introduction). For instance, some programs have been used to learn medical diagnostic rules from a database of patients whose diagnoses are known. These programs examine a number of attributes (e.g. age, temperature, and pulse rate) for a set of exa...