多层高效用品套装隐藏多层高效用品套装
Loan T T Nguyen1,2, Hoa Duong1,2, An Mai1,2
1School of Computer Science and Engineering, International University, Ho Chi Minh City, Vietnam.
PloS one
|February 3, 2025
概括
新的保护隐私的实用挖掘算法,MLHProtector和FMLHProtector,在所有抽象级别保护敏感的高实用项目集,防止数据从交易数据库泄露.
科学领域:
- 数据挖掘 数据挖掘
- 信息安全 信息安全
- 数据库管理数据库管理
背景情况:
- 数据隐私是一个关键问题,特别是交易数据库中的敏感信息.
- 高实用项目集采矿 (HUIM) 识别了有价值的模式,但可以暴露敏感数据.
- 现有的保护隐私的公用事业挖掘 (PPUM) 方法往往忽略了数据概括,使更高的抽象级别变得脆弱.
研究的目的:
- 开发新的PPUM算法,以保护所有抽象级别的敏感高实用性项目集.
- 为了解决目前的PPUM技术的局限性,这些技术只专注于专门的项目级别.
- 加强组织共享交易数据的数据安全性.
主要方法:
- 引入了两个新的PPUM算法:MLHProtector和FMLHProtector.
- 设计算法,以便在多个层次的数据抽象中有效运行.
- 在保护敏感项目的算法性能上的实证评估.
主要成果:
- MLHProtector和FMLHProtector成功地保护敏感的高效用品集免受未经授权的发现.
- 拟议的算法确保了数据在各种抽象级别的保密性.
- 实验结果验证了开发的PPUM技术的有效性.
结论:
- 开发的MLHProtector和FMLHProtector算法为交易数据库中的高实用性项目集提供了强大的隐私保护.
- 解决所有抽象级别对于在实用采矿中全面维护隐私至关重要.
- 这些算法在保护敏感业务数据免受数据挖掘威胁方面取得了重大进展.
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