ABSTRACT Data stream mining is a technique to obtain the useful informat ion by analyzing the data generated in real time. In data stream mining technology, frequent itemset mining is a method t o find the frequent itemset while data is transmitting, and these itemsets are used for the purpose of pattern analyze and marketing in various fields. Existing techniques of finding frequent itemset mining are having problems when a malicious at tacker sniffing the data, it reveals data provider’s real-time information. These problems can be solved by using a method of inserting dummy data. By using this method, a attacker cannot distinguish the original data from the transmitting data . In this paper, we propose a method for privacy preserving frequent itemset mining by using the technique of inserting dum my data. In addition, the proposed method is effective in terms of calculation because it does not require encryption technolog y or other mathematical operations.Keywords: Data Stream, Privacy Preserving, Frequent Itemset mining접수일(2013년 3월 28일), 수정일(2013년 4월 30일), 게재확정일(2013년 5월 1일)* 이 논문은 2012년도 정부(교육과학기술부)의 재원으로 한국연구재단의 지원을 받아 수행된 기초연구사업임(20120007037)†주저자, blue7angels@korea.ac.kr‡교신저자, irjeong@korea.ac.kr (Corresponding author)