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Yang, Ying, Yang, Lina, Yang, Meihong, Yu, Huanhuan, Zhu, Guichun, Chen, Zhenya, Chen, Lijuan.  2019.  Dark web forum correlation analysis research. 2019 IEEE 8th Joint International Information Technology and Artificial Intelligence Conference (ITAIC). :1216—1220.

With the rapid development of the Internet, the dark network has also been widely used in the Internet [1]. Due to the anonymity of the dark network, many illegal elements have committed illegal crimes on the dark. It is difficult for law enforcement officials to track the identity of these cyber criminals using traditional network survey techniques based on IP addresses [2]. The threat information is mainly from the dark web forum and the dark web market. In this paper, we introduce the current mainstream dark network communication system TOR and develop a visual dark web forum post association analysis system to graphically display the relationship between various forum messages and posters, and help law enforcement officers to explore deep levels. Clues to analyze crimes in the dark network.

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Yang, Ying, Yu, Huanhuan, Yang, Lina, Yang, Ming, Chen, Lijuan, Zhu, Guichun, Wen, Liqiang.  2019.  Hadoop-based Dark Web Threat Intelligence Analysis Framework. 2019 IEEE 3rd Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC). :1088—1091.

With the development of network services and people's privacy requirements continue to increase. On the basis of providing anonymous user communication, it is necessary to protect the anonymity of the server. At the same time, there are many threatening crime messages in the dark network. However, many scholars lack the ability or expertise to conduct research on dark-net threat intelligence. Therefore, this paper designs a framework based on Hadoop is hidden threat intelligence. The framework uses HDFS as the underlying storage system to build a HBase-based distributed database to store and manage threat intelligence information. According to the heterogeneous type of the forum, the web crawler is used to collect data through the anonymous TOR tool. The framework is used to identify the characteristics of key dark network criminal networks, which is the basis for the later dark network research.