Machine Learning-Based Phishing Attack Detection

Rule-Based Phishing Attack Detection

The World Wide Web has become the hotbed of a multi-billion dollar underground economy among cyber criminals whose victims range from individual Internet users to large corporations and even government organizations. As phishing attacks are increasingly being used by criminals to facilitate their cyber schemes, it is important to develop effective phishing detection tools. In this paper, we pro...

Detection of Phishing Attacks: A 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...

An Evaluation of Machine Learning-Based Methods for Detection of Phishing Sites

In this paper, we evaluate the performance of machine learningbased methods for detection of phishing sites. In our previous work [1], we attempted to employ a machine learning technique to improve the detection accuracy. Our preliminary evaluation showed the AdaBoost-based detection method can achieve higher detection accuracy than the traditional detection method. Here, we evaluate the perfor...

Phishing Website Detection based on Supervised Machine Learning with Wrapper Features Selection

The problem of Web phishing attacks has grown considerably in recent years and phishing is considered as one of the most dangerous Web crimes, which may cause tremendous and negative effects on online business. In a Web phishing attack, the phisher creates a forged or phishing website to deceive Web users in order to obtain their sensitive financial and personal information. Several conventiona...