Alarm correlation plays an important role in improving the service and reliability in modern telecommunication networks. Most previous research of alarm correlation didn’t consider the effects of noise data in the database. This paper focuses on the method of discovering alarm correlation rules from the database containing noise data. We firstly define two parameters Win_freq and Win_add as the measures of noise data and then present the Robust_search algorithm to solve the problem. At different size of Win_freq and Win_add, the experiments on alarm database containing noise data show that the Robust_search Algorithm can discover more rules with the bigger size of Win_add. We also compare two different interestingness measures of confidence and correlation by experiments. Keywords Alarm Correlation, Noise Data, Alarm Model, Network Management, Data Mining, Correlation Rules, Interestingness Measure