1. 国网江苏省电力有限公司
2. 国网思极网安科技(北京)有限公司
纸质出版:2025
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李新家, 张崇超, 马云龙, 等. 一种面向复杂业务场景的多源异构数据分类分级方法研究[J]. 电力信息与通信技术, 2025,23(6):48-57.
李新家, 张崇超, 马云龙, et al. 一种面向复杂业务场景的多源异构数据分类分级方法研究[J]. 2025, 23(6): 48-57.
李新家, 张崇超, 马云龙, 等. 一种面向复杂业务场景的多源异构数据分类分级方法研究[J]. 电力信息与通信技术, 2025,23(6):48-57. DOI: 10.16543/j.2095-641x.electric.power.ict.2025.06.07.
李新家, 张崇超, 马云龙, et al. 一种面向复杂业务场景的多源异构数据分类分级方法研究[J]. 2025, 23(6): 48-57. DOI: 10.16543/j.2095-641x.electric.power.ict.2025.06.07.
数据分类分级是制定有效数据安全策略和措施的基础,目前相关方法研究主要适用于同构数据,且受主观因素的干扰,影响了分类分级的准确性。面对日益复杂、多样化、共享开放的业务场景,文章提出了一种基于决策树算法和模糊控制算法的多源异构数据分类分级方法,该方法首先运用决策树算法和线性分类法对源数据进行初步分类,通过构建决策树模型将数据精准地划分到不同的类别中,为后续数据的分级处理奠定基础;然后基于前期数据处理的结果,进一步采用模糊控制算法,根据数据在各个安全要素上的需求差异,对每个数据类别进行更为细致的分级;最后,根据不同级别数据的安全需求,选择相应的数据安全策略。实验结果表明,该方法在处理多源异构数据的分类分级问题上,具有较好的准确率和效率,使得该方法能够有效应对各种复杂业务场景下的数据分类分级需求。
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