企业外网应用系统在线评估研究与测试

Online Assessment Research and Testing of the Application System of Enterprise External Network

企业外网应用系统作为企业面向社会和外部企业运营的通道,在提高企业运营效率的同时面临着来自互联网安全危险。因此研究实时在线信息安全评估与分析具有很重要的作用。本文结合企业互联网应用系统面临的信息安全现状,研究基于强化学习的WEB信息抓取RLC模型,通过模型来完成WEB页面结构化、页面特征提取、链接特征抽取等任务,同时利用综合回报评价模型中的Q值评价算法评价链接的接口相关度,根据该接口相关度数值进行WEB信息抓取对象选择,为WEB信息抓取提供最优选择策略,减少对无效页面检测的次数,从而提高整体安全检测效率。

Outside the enterprise network as an enterprise application system geared to the needs of society and ex-ternal enterprise operating channels. At the same time,the improvement of operational efficiency of enterprises is faced with network security risk. So the online assessment and analysis on information security is of vital impor-tance. Together with the present situation of Guangdong power grid application system facing internet information security ,the Web information fetching RLC model of reinforcement learning was studied to complete the struture of Web page,the extraction of page and links features,etc. . Meanwhile,the Q-value comprehensive evaluation model of return correlation algorithm evaluates the link interface,through the interface relevance for WEB information grasping object selection,the optimum choice for WEB information fetching strategy,and reduces the number of in-valid pages detection,thus improving the overall safety detection efficiency.