C-SWF Incremental Mining Algorithm for Firewall Policy Management__臺灣人文及社會科學引文索引資料庫

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題名：	C-SWF Incremental Mining Algorithm for Firewall Policy Management
書刊名：	資訊、科技與社會學報
作者：	Chang, Ray-i／Chang, Keng-wei
出版日期：	2009
卷期：	16
頁次：	頁45-61
主題關鍵詞：	Computer security；Firewall；Policy management；Data mining；Association rule
原始連結：	連回原系統網址
相關次數：	被引用次數:期刊(1) 博士論文(0) 專書(0) 專書論文(0) 排除自我引用:1 共同引用:0 點閱:30

As the number of security incidents had been sharply growing, the issue of security-defense draws more and more attention from network community in past years. Firewall is known as one of the most popular security-defense mechanism for corporations. It is the first defense-line for security infrastructure of corporations to against external intrusions and threats. A firewall will filter packets by following its policy rules to avoid suspicious intruder executing illegal actions and damaging internal network. Well-designed policy rules can increase the security-defense effect to against security risk. In this paper, we apply association rule mining to analyze network logs and detect anomalous behaviors, such as connections those shown frequently in short period with the same source IP and port. From these anomalous behaviors, we could inference useful, up-to-dated and efficient firewall policy rules. Comparing with the method proposed in [18], we utilize incremental mining to handle the increasingly changed traffic log data. The proposed method can highly enhance the execution performance in data analyzing. Experimental results show that the execution efficiency of our method is better than that of traditional methods when dealing with large-sized log files.

以文找文

期刊論文
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會議論文
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圖書
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1.	(2004)。Five Mistakes of Security Log Analysis。
2.	CERT / COMPUTER EMERGENCY READINESS TEAM。CERT/CC Statistics 1988-2003 – incidents reported。
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4.	Gordon, L. A.，Loeb, M. P.，Lucyshyn, W.，Richardson, R.(2005)。2005 CSI/FBI Computer Crime and Security Survey。

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