String matching plays a fundamental role in many network security applications such as NIDS, virus detection and information filtering. In this paper, we proposed cache-efficient methods to accelerate classical multiple string matching algorithms. We observed that most classical algorithms perform poorly as pattern set grows due to their high memory requirement and the poor cache behavior. Based on this observation, we proposed efficient methods employing cache-efficient strategies, i.e., to accelerate string matching by minimizing memory usage and maximizing cache locality. Experimental results on random datasets demonstrated that our new methods are substantially faster than classical methods.