基于行为分析的内网数据防泄露场景研究与技术实现

Research and Technical Implementation of Intranet Data Leakage Prevention Scenarios Based on Behavior Analysis

通过对内网数据泄露场景的研究,基于行为分析技术发现内网数据泄露的风险。从内网数据的生命周期出发,结合内网数据泄露的途径,梳理出45个数据泄露的场景。采用基于分析规则的流式实时分析和基于AI检测的离线行为建模分析两种方法对场景进行检测。目前已将这些研究成果成功应用于数据防泄露监测平台,取得了令人满意的效果,为解决内网数据防泄露问题提供了一种新的研究思路和实践方法。

Through the research of intranet data leakage scenarios,behavioral analysis based technologies can identify the risk of intranet data leakage.Starting from the lifecycle of intranet data and combining the pathways of intranet data leakage,45 data leakage scenarios are identified.The rule-based streaming realtime analysis method and the AI detection-based offline behavior modeling analysis method are employed to detect the scenarios.Currently,these research findings have been successfully applied to the data leakage prevention and monitoring platform with satisfactory results,which provides a new research idea and practical method for addressing the problem of intranet data leakage prevention.