Phishing Attacks Detection Using Genetic Programming

Phishing is a real threat on the Internet nowadays. According to a report released by an American security firm, RSA, there have been approximately 33,000 phishing attacks globally each month in 2012, leading to a loss of $687 million. Therefore, fighting against phishing attacks is of great importance. One popular and widely-deployed solution with browsers is to integrate a blacklist sites into them. However, this solution, which is unable to detect new attacks if the database is out of date, appears to be not effective when there are a lager number of phishing attacks created very day. In this paper, we propose a solution to this problem by applying Genetic Programming to phishing detection problem. We conducted the experiments on a data set including both phishing and legitimate sites collected from the Internet. We compared the performance of Genetic Programming with a number of other machine learning techniques and the results showed that Genetic Programming produced the best solutions to phishing detection problem.