暗网环境下恐怖主义信息挖掘与分析

随着互联网和人工智能的快速发展,恐怖主义活动方式变得更为隐秘。网络恐怖主义活动空间从表网的在线社区与视频分享平台转向暗网黑市交易和暗网论坛。针对暗网节点通信和交易信息高度匿名等特点,相应的反恐工作需要采取新的技术手段,以深度切入恐怖分子用于扩大影响的暗网空间。为此,可以设计和优化专门适用于暗网的聚焦爬虫工具,挖掘恐怖主义活动信息;可以搭建涉恐事件数据模型,分析恐怖组织可能的线下攻击手段;可以利用社会网络分析和超链接分析方法,定位暗网内恐怖主义隐蔽社区和危险用户集群。通过准确把握暗网中的匿名恐怖主义活动规律,抓住安全监控与防范的重点、难点,综合施策,以及适时制定和精准实施反恐网络安全策略,能够最大限度遏制暗网恐怖主义的危害,保护国家安全和人民利益。

Terrorism Information Mining and Analysis in the Dark Web

With the rapid development of the Internet and artificial intelligence,there are more underground terrorist activities than ever.The forms of cyber-terrorist activities have changed from online and offline campaign,recruitment,trading and financing to social media interactions such as Facebook,Instagram,Twitter,and YouTube.Terrorists are now more active in the dark web black market and dark web forums than online communities and video-sharing platforms.As anonymity of communication and transaction is the most important characteristic of the dark web,anti-terrorism efforts need to adopt new technological means to penetrate deeply into the dark net space used by terrorists.Thus,the focused crawler especially for the dark web could be used to track terrorist activities and other information.Hypothesis theory and game theory could be used to build the data model of terrorism-related events to analyze the possible offline attacks.Social network analysis and hyperlink analysis could be adopted to locate terrorist hidden communities and dangerous user clusters in the dark web.By learning the patterns of anonymous terrorist activities in the dark web,identifying the difficulties in monitoring and prevention,China could take comprehensive measures,and timely formulate and accurately implement anti-terrorism network security policies.In this way,dark web terrorism could be contained to the maximum extent while the national security and people’s interests will be secured.