面向工业数据流场景的可配置规则引擎

Fangning Shi, Zhong Na, Zhifeng Gao
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引用次数: 0

摘要

随着新一代信息技术与工业的融合,工业数据的价值被高度重视。同时,企业也面临着各种数据安全威胁,迫切需要建立可信可控的工业数据流通平台和生态系统,消除企业顾虑,释放数据元素共享流通的活力。本文利用主成分分析对数据集进行分类、过滤、变换或处理,支持预警规则的配置。随后,基于可配置的规则引擎,执行安全策略验证和异常行为预警,实现对整个数据流通过程的实时监管和跟踪,及时发现和预警风险行为,避免数据泄露风险,保障数据流通安全。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Configurable Rule Engine for Industrial Data Flow Scenarios
With the integration of new generation information technology and industry, the value of industrial data has been highly valued. Meanwhile, enterprises are also facing various data security threats and urgently need to establish a trusted and controllable industrial data circulation platform and ecosystem, to eliminate enterprise concerns, unleash the vitality of data element sharing and circulation. This paper uses principal component analysis to classify, filter, transform or process the dataset, supporting the configuration of warning rules. Subsequently, based on a configurable rule engine, security policy verification and abnormal behavior warning are executed to achieve real-time supervision and tracking of the entire data circulation process, timely discover and warn of risk behaviors, avoid the risk of data leakage and protect data circulation security.
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