Improved Hybrid Model for Phishing Detection by Using Machine Learning

Modern word is revolutionized since decades due to the rapid increment in online technologies. As online transaction and business growing rapidly security problem also become a challenges for all over the world. Among the different security threats phishing is most popular and dangerous threats that need to be tackle as soon as happened. Attacker steals the personal information of the user through phishing websites about which the user is unaware. Many mechanism has been proposed to tackle with these phishing attacks but there is still need an approach that perform best in detection of that attacks. In this paper a hybrid model is proposed for the detection of phishing attacks and datasets are taken from UCI repository. In this hybrid model different algorithms are applied on the datasets through Weka and Rapid Minor software. After the results of individual we compare the performance the best features algorithms in order to take less error rate and high accuracy.