Recently the act of fraud aimed at the air tickets is more and more rampant. Lawbreakers get passenger information from illegal channels, not only make a lot of passengers suffering financial loss, but also influence the reputation and business of airline. There are many ways that passenger information easy to be leaked, in this paper, we just focus on the detection of abnormal access behaviors that hacker intrudes the frequent passenger system to get the passenger information. In this paper, we analyze the passenger’s behavior of visiting the frequent passenger system deeply. Then we base on the naïve bayes algorithm to detect the behavior of passengers, so that we can decide whether the account is abnormal. Through the experiment and evaluation, we demonstrate that our approach is effective to identify the illegal log in of hackers and makes a great help in improving the security of passenger information.