大数据技术在数据安全治理中的应用

Application of big data technology in data security governance

面对新形势下的数据安全治理挑战,顺应数据安全领域的技术发展趋势,针对大型国企在数据安全治理实际应用中突出的关键权限人员识别问题,提出了一种基于图算法的关键权限人员识别技术。该技术可以发现系统中潜在的权限影响因素,并可从多个角度衡量不同含义的权重影响力,识别结果可解释性强。针对数据安全治理中的用户与实体行为异常检测问题,提出一种基于生成对抗网络的用户与实体行为异常检测方法,实验结果表明,所提方法的精确率、召回率和F1值的平均值均优于对比基线模型方法。设计开发了数据安全平台,平台在降低数据安全风险、辅助企业合规建设、促进数据开发利用等方面起到了重要作用,已在多个数据集中管理项目中得到应用,能满足安全场景下的大数据处理需求,具有较好的应用推广价值。

Facing the challenges of data security governance in the new situation and following the technological development trends in the field of data security,in response to the prominent issue of identifying key authorized personnel in the practical application of data security governance in large state-owned enterprises,this article proposes a key authorized personnel identification technology based on graph algorithm,which can discover potential authorization influencing factors in the system and measure the weight influence of different meanings from multiple perspectives,The recognition results have strong interpretability.Aiming at the problems of user and entity behavior anomaly detection in data security governance,this paper proposes a user and entity behavior anomaly detection method based on the generative adversarial network.The experimental results show that the accuracy,recall rate and average F1-score of the proposed method are better than the comparison baseline model method.A data security platform has been designed and developed.The platform has played an important role in reducing data security risks,assisting enterprise compliance construction,promoting data development and utilization,and has been applied in multiple data centralized management projects.It can meet the needs of big data processing in security scenarios,and has good application and promotion value.