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Recently, cyber terrors are increasing in their frequencies and scales, for example, 3.4 DDoS and 4.12 APT attack to NH Bank, and consequently in the damage. The recent cyber attacks are characterized by being conducted under specific goals by certain individuals or group of people, using diversified methods, over a long time to invade the target system. The goals include pecuniary and political profits. The kinds of malware which discloses private, credit, or financial information are ever increasing, followed by the secondary damage including appropriation of others names and financial frauds. In case of such invasion cases, fast detection of the malware in the system under attack is necessary. However, the response technologies cannot catch up with the development of malware and it takes time and efforts to handle intrusion cases. This paper proposes a correlation analysis detection technology based on a new concept to help faster and correct detection of malware in infected PCs.