This paper proposes an efficient anti-keyword derivation method to improve the rejection performance of keyword spotting. In this method, each anti-keyword is derived from the large vocabulary lexicon considering acoustic similarity to keywords, making use of the confusion matrix. Experimental results show that a 3% improvement of the rejection rate is obtained compared to conventional methods that do not have our anti-keyword models.