Feretzakis Georgios, Kalles Dimitris, Verykios Vassilios S
School of Science and Technology, Hellenic Open University, Patras 263 35, Greece.
Stud Health Technol Inform. 2020 Jun 26;272:99-102. doi: 10.3233/SHTI200503.
Data sharing has become an increasingly common process among health organizations, but any organization will most likely try to hide some sensitive patterns before sharing its data with others. Local Distortion Hiding (LDH), a recently proposed algorithm, has been evaluated only on the assumption of an opponent using the J48 (C4.5) classification algorithm. We now extend the basic approach, and we present a medical dataset hiding case study of a processed by LDH and attacked with the CART algorithm.
数据共享在卫生组织之间已成为越来越普遍的过程,但任何组织在与其他组织共享其数据之前很可能会试图隐藏一些敏感模式。局部失真隐藏(LDH)是一种最近提出的算法,目前仅在对手使用J48(C4.5)分类算法的假设下进行了评估。我们现在扩展了基本方法,并展示了一个经过LDH处理并受到CART算法攻击的医学数据集隐藏案例研究。