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Proxy Servers are tools that are used to facilitate clients for accessing websites. Proxy Servers uses cache to stored visited sites in order to deliver faster web accesses to users, without requesting to external target servers. With the limitation of cache size, however, a number of techniques have been proposed to potentially increase the performance of cache replacement methods. This paper applies a data mining technique to generate frequent itemsetpatterns of the internet access by users. Data transactions are generated based on the allocated time slots of internet usage. As the public the Internet cluster, different users can use the same single computer; therefore, generating data transaction base on computer IP may not extract the behavior of users. Association rules are generated using FP-growth algorithm. The frequent itemsets (rules) are then used to implement and extension of LRU cache-replacement technique. The experimental results show that the proposed technique provides promising result and is superior to the base-line cache replacement techniques (i.e. FIFO and LRU).

Proxy Server Systems Improvement Using Frequent Itemset Pattern-Based Techniques