A Phishing URL Classification Technique using Machine Learning Approach

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...

Detection of Phishing Attacks: A Machine Learning Approach

A Method for Classification Using Machine Learning Technique for Diabetes

Machine learning has been one of the standard and improving techniques with strong methods for classification and reorganization based on recursive learning. Machine learning allows to train and test classification system, with Artificial Intelligence. Machine learning has provided greatest support for predicting disease with correct case of training and testing. Diabetes needs greatest support...

Online Learning for URL classification

This work consists of a review of online algorithms for URL classification followed by some extensions and tweaking of these methods to make them efficient in terms of computational time and memory. We found out that the trade-off in error for these extensions are fairly comparable for some of these algorithms. We also applied two more kernel based methods namely Forgetron and Projectron.