基于暗网的反恐情报分析研究

Research on Analysis of Counter-terrorism Intelligence Based on Dark Web

[目的/意义]对暗网概念、特征、暗网反恐情报的意义及分析方法进行论述,为反恐情报研究引入新的内容和方法。[方法/过程]通过文献调研、内容分析等方法,在对国内外暗网反恐情报分析相关研究进行系统梳理的基础上,提出暗网反恐情报分析的流程,并设计暗网反恐情报分析平台架构,对主要分析方法、关键技术、分析工具及未来研究重点进行详细论述。[结果/结论]暗网反恐情报对支持反恐预警、控制恐怖舆论传播、为涉恐案件侦查提供线索及证据、指导反恐行动资源优化配置等方面具有重要意义;暗网反恐情报分析流程包括:恐怖组织特征识别、数据获取与信息过滤、机器学习与智能分析、人工分析与情报研判、情报生成与成果传递五个环节;暗网反恐情报"深度"分析、暗网反恐情报共享、公民网络隐私权保护将成为未来的研究热点。

[Purpose/Significance]This paper primarily discusses the concept,characteristics,significance and analysis methods of dark net counter-terrorism information,and introduces newcontents and methods for counter-terrorism intelligence research.[Method/Process]Through literature research and content analysis,this paper illustrates the research status of dark net counter-terrorism information analysis,analysis processes,important methods,technologies,analysis tools,analysis platform and explains the future research focus.[Result/Conclusion]Dark net counter terrorism intelligence is of great significance for supporting the early warning of terrorism,controlling the spread of terrorist public opinion,providing clues and evidence for investigating terrorism related cases,and providing guidance for optimizing the allocation of resources for counter-terrorism operations. The dark net intelligence analysis process mainly includes： terroristic organization feature recognition,data acquisition and information filtering,machine learning and intelligence analysis,artificial analysis and intelligence determine,intelligence generation and achievement transfer. The deep analysis of counter terrorist intelligence in dark web,the sharing of counter-terrorism intelligence in dark network and the protection of privacy in civil network will become the hot research topic in the future.