• KIPS Transactions on Computer and Communication Systems
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• v.1 no.1
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• pp.55-60
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• 2012

Recent botnets are widely using the DNS services at the connection of C&C server in order to evade botnet's detection. It is necessary to study on DNS analysis in order to counteract anomaly-based technique using the DNS. This paper studies collection of DNS traffic for experimental data and supervised learning for DNS traffic-based malicious domain classification such as query of domain name corresponding to C&C server from zombies. Especially, this paper would aim to determine significant features of DNS-based classification system for malicious domain extraction by the Principal Component Analysis(PCA).

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.3
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• pp.659-666
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• 2012

Recently, cloud computing service has become a rising issue in terms of utilizing sources more efficiently and saving costs. However, the service still has some limitations to be popularized because it lacks the verification towards security safety. In particular, the possibility to induce Denial of service is increasing as it is used as Zombie PC with exposure to security weakness of Guest OS's. This paper suggests how cloud system, which is implemented by Xen, detects intrusion caused by Denial of service using hypercall. Through the experiment, the method suggested by K-means and EM shows that two data, collected for 2 mins, 5 mins, 10mins and 20mins each, are distinguished 90% when collected for 2mins and 5mins while collected over 10mins are distinguished 100% successfully.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.10
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• pp.1808-1814
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• 2008

In addition to RBL function, which is used to applying for spam e-mail filtering, as an effective way to deal with the recently widespread spam types, this paper proposes how to extract URL that was comprised in the original e-mail, apply it to RBL, and expand it. The BotNet, which is used to using for sending spam mails these days, has a problem that it is not able to solve with the distributed addresses of sent mails in spam e-mails. In general, as these spam e-mails are sent from the infected Zombi PC of individual user, the sent address itself is not efficient and is meaningless to use in RBL. As an effective way to filter spam e-mail sent by BotNet, this paper analyzes URLs that contained in the original spam e-mail and proposes how to effectively improve filter rate, based on the distribution data of URL site tempting users. This paper proposes the sending mechanism of spam e-mails from BotNet and the methods to realize those types of spam e-mails. In order to gather analyzable spam e-mails, this paper also carries out an experiment by configuring trap system of spam e-mail. By analyzing spam e-mails, which have been received during the certain period of experiment, this paper shows that the expanded RBL method, using URLs that contained in spam e-mails, is effective way to improve the filter distribution of spam e-mail.