Abstract:
This paper focuses on the privacy preserving sequential patterns mining in the following situation: (1)multiple parties; (2)each has a private data set; (3) wish to collaboratively discover sequential patterns on the union of the multiple private data sets without disclosing their private data to each other. It puts forward a novel approach to discover privacy-preserving sequential patterns based on secure multi-party computation by using commutative encryption and homomorphic encryption technology.
Key words:
commutative encryption,
homomorphic encryption,
secure multi-party computation,
privacy preserving sequential patterns mining
摘要: 研究了以下情况下的私密保持序贯模式挖掘:(1)多方参与;(2)每方均有自己的私有数据集;(3)要求在这多个水平划分的私有数据集的并集上多方合作挖掘序贯模式,同时各方均不向其他方泄露自己的私有数据信息。利用可交换加密技术和同态加密技术,提出一个新颖的基于安全多方计算的私密保持序贯模式挖掘算法。
关键词:
可交换加密技术,
同态加密,
多方安全计算,
私密保持序贯模式挖掘
CLC Number:
ZHANG Wen-yan; OUYANG Wei-min. Privacy Preserving Sequential Patterns Mining on Horizontally Partitioned Data[J]. Computer Engineering, 2007, 33(19): 170-172.
张文燕;欧阳为民. 水平划分数据的私密保持序贯模式挖掘[J]. 计算机工程, 2007, 33(19): 170-172.