Packet filtering plays a critical role in many of the current high speed network technologies such as firewalls and IPSec devices. The optimization of firewall policies is critically important to provide high performance packet filtering particularly for high speed network security. Current packet filtering techniques exploit the characteristics of the filtering policies, but they do not consider the traffic behavior in optimizing their search data structures. This results in impractically high space complexity, which undermines the performance gain offered by these techniques. Also, these techniques offer upper bounds for the worst case search times; nevertheless, average case scenarios are not necessarily optimized. Moreover, the types of packet filtering fields used in most of these techniques are limited to IP header fields and cannot be generalized to cover transport and application layer filtering.In this paper, we present a novel technique that utilizes Internet traffic characteristics to optimize firewall filtering policies. The proposed technique timely adapts to the traffic conditions using actively calculated statistics to dynamically optimize the ordering of packet filtering rules. The rule importance in traffic matching as well as its dependency on other rules are both considered in our optimization algorithm. Through extensive evaluation experiments using simulated and real Internet traffic traces, the proposed mechanism is shown to be efficient and easy to deploy in practical firewall implementations.
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