Abstract: Phishing E-mail detection methods are mostly focused on the extraction of different E-mail features, which lead the time increasing. To solve this problem, a method based on density and distance was proposed. The method replaces the 42 original mail features with 2 new ones, i.e., features based on density and distance. Then the machine learning classification algorithm was used to detect phishing E-mail. The detection accuracy of the proposed method reaches 99.74%, and time is only 3.39 s, which is 1/20 of the traditional algorithm. Results show that the algorithm has a better detection performance and saves much time.