文章摘要
大数据环境下的微信息蜜罐监测
Research about Micro-message Honeypot Detection Base on Big Data
  
DOI:
中文关键词: 自媒体  舆情检测  蜜罐  虚拟机  进程级检测
英文关键词: we-media  public opinion test  honey-pots  virtual machine  process detection
基金项目:教育部人文社会科学研究资助项目(14YJA860017;16XJJAZH003);国家自然科学基金资助项目(61562080);新疆高校科学研究重点资助项目(XJEDU2016I064;XJEDU2017M025)
作者单位
孙彬1,王东1,2 1.新疆财经大学 计算机科学与工程学院,新疆 乌鲁木齐 830011
2.新疆教育学院 新疆教育云重点实验室,新疆 乌鲁木齐 830033 
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中文摘要:
      互联网自媒体呈现大数据特征,负能量言行时常爆发,舆情检测已经成为网络监管的重大难点问题.本文基于软件定义网络、蜜罐技术和分布式架构,综合“流量级”检测和“进程级”检测2个层面,通过构造异常行为数据集和敏感文本类型数据集,设计负能量舆情倾向的检验算法,搭建虚拟蜜罐式主动性舆情检测系统.实践证明,虚拟蜜罐式主动舆情检测系统,能较好地完成自媒体圈的主题倾向监测任务,为自媒体圈舆情检测技术提供新的研究视角.
英文摘要:
      The internet we-media has large data characteristics, and negative energy words and deeds often break out. So public opinion detection becomes a major and difficult problem in network regulation. Based on software definition network, honeypot technology and distributed architecture, integrates "traffic level" detection and "process level" detection two levels, then negative energy public opinion test algorithm was designed and a virtual honeypot active public opinion detection system through constructing the exception behavior data set and the sensitive text type data set. Practice proved that virtual honeypot active public opinion detection system can better complete the thematic tendency monitoring tasks from we-media circle, and it can provide a new perspective for public opinion detection technology from we-media circle.
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