AI图景下基于大数据挖掘的风险评估研究  

Research on risk assessment based on big data mining in AI landscape

作　　者：王伟[1] Wang Wei(Department of information engineering,Henan Industry and Trade Vocational College,Zhengzhou Henan,451191)

机构地区：[1]河南工业贸易职业学院信息工程系,河南郑州451191

出　　处：《电子测试》2020年第21期84-85,116,共3页Electronic Test

基　　金：河南省科技攻关项目.省级(182102210021);河南省高等学校重点科研项目.厅级(18A520014);河南省高等学校重点科研项目计划支持(21B520004)。

摘　　要：随着网络数据体量的增加,AI图景中隐含的风险因素增多,加重了AI图景的使用风险,威胁各个行业与工作领域。而传统方法由于获取风险因素的静态关联规则,当数据体量不断上涨时,其风险等级评估结果严重脱离实际,因此研究AI图景下,基于大数据挖掘的风险评估方法。此次评估基于大数据挖掘,获取风险因素动态关联规则;利用云模型,粒化AI图景;根据评估矩阵,评估AI图景的使用风险。实验证实数据体量不断增长条件下,此次研究方法的风险评估结果,与给定结果一致。可见此次研究的风险评估方法,可用来测量AI图景的使用风险。With the increase of network data volume,there are more risk factors in AI landscape,which aggravates the use risk of AI landscape and threatens various industries and work fields.However,traditional methods get static association rules of risk factors,and when the volume of data continues to rise,its risk level assessment results are seriously divorced from reality.Therefore,the risk assessment method based on big data mining in AI scenario is studied.The assessment is based on big data mining to obtain the dynamic association rules of risk factors;the cloud model is used to granulate the AI landscape;and the evaluation matrix is used to evaluate the use risk of AI landscape.The experimental results show that the risk assessment results of this research method are consistent with the given results under the condition of increasing data volume.It can be seen that the risk assessment method of this study can be used to measure the use risk of AI landscape.

关 键 词：AI图景 大数据挖掘 风险评估 动态关联规则 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论] TP18[自动化与计算机技术—计算机科学与技术]