摘要
个性化采集策略是有效监测复杂网络环境面临的威胁的必要条件之一,然而安全需求和威胁类型差异等导致难以有效生成个性化的采集策略。针对上述问题,设计了面向威胁监测的采集策略自动精化方法。首先,提出了采集策略层次模型;然后,将威胁类型到采集项的精化转化为采集收益和采集成本平衡的非线性优化问题,并利用遗传算法进行求解;最后,通过模拟实验,验证可根据高层监测需求自动生成采集方案。
Personalized collect policy is one of the necessary conditions for effectively monitoring threats in the complex network environment. However, differences in security requirements and threat types make it difficult to effectively generate personalized collect policy. To address the above problem, a collection policy automatic refinement method was designed. Firstly, a hierarchical model of collection policy was proposed. Then, by transforming the policy refinement into a nonlinear optimization problem, a genetic algorithm was designed to balance between collection revenue and collection cost. Finally, simulation experiments verify that according to the requirements of high-level monitoring, the acquisition scheme can be automatically generated.
作者
李凤华
李子孚
李凌
张铭
耿魁
郭云川
LI Fenghua;LI Zifu;LI Ling;ZHANG Ming;GENG Kui;GUO Yunchuan(Institute of Information Engineering,Chinese Academy of Sciences,Beijing 100093,China;School of Cyber Security,University of Chinese Academy of Sciences,Beijing 100049,China;Science and Technology on Communication Networks Laboratory,Shijiazhuang 050081,China;School of Cyber Engineering,Xidian University,Xi’an 710071,China)
出处
《通信学报》
EI
CSCD
北大核心
2019年第4期49-61,共13页
Journal on Communications
基金
国家重点研发计划基金资助项目(No.2016YFB0801001)
国家自然科学基金资助项目(No.61672515)
中国科学院大学生创新实践训练计划基金资助项目~~
关键词
数据采集
威胁监测
策略精化
混合优化
data collection
threat monitoring
policy refinement
hybrid optimization
