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Erschienen in:
2017 | OriginalPaper | Buchkapitel
Detecting Black IP Using for Classification and Analysis Through Source IP of Daily Darknet Traffic
verfasst von : Jinhak Park, Jangwon Choi, Jungsuk Song
Erschienen in: Neural Information Processing
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Abstract
Recently, the community is recognizing to an importance of network vulnerability. Also, through the using this vulnerability, attackers can acquire the information of vulnerable users. Therefore, many researchers have been studying about a countermeasure of network vulnerabillty. In recent, the darknet is a received attention to research for detecting action of attackers. The means of darknet are formed a set of unused IP addresses and no real systems of connect to the darknet. In this paper, we proposed an using darknet for the detecting black IPs. So, it was choosen to classification and analysis through source IP of daily darknet traffic. The proposed method prepared 8,192 destination IP addresses in darknet space and collected the darknet traffic during 1 months. It collected total 277,002,257 in 2016, August. An applied results of the proposed process were seen for an effectiveness of pre-detection for real attacks.