Towards comprehensive support for privacy preservation cross-organization business process mining
Document Type
Article
Publication Date
7-1-2019
Abstract
More and more business requirements are crossing organizational boundaries. There comes the cross-organization business process management, and its modeling is a complicated task. Mining a cross-organization business process aims to discover its model from a set of distributed event logs. Unfortunately, traditional process mining approaches totally neglect the privacypreservation issue, which means the privacy of both event log and business process model. In this paper, a privacy-preservation crossorganization business process mining framework is proposed to handle its privacy issues. It includes three steps: (1) each organization discovers its private and public business process models from its event logs; (2) the trusted third-party midware takes the public process models as input and generates cooperative public process model fragments of each organization; and (3) each organization combines its private business process model with its relevant public fragments to obtain the organization-specific cross-organization cooperative business process model. To illustrate the applicability of the proposed approach, a multi-modal cross-organization transportation case is used for its validation and comparison with other methods.
Identifier
85099890375 (Scopus)
Publication Title
IEEE Transactions on Services Computing
External Full Text Location
https://doi.org/10.1109/TSC.2016.2617331
e-ISSN
19391374
First Page
639
Last Page
653
Issue
4
Volume
12
Grant
BS2014DX013
Fund Ref
National Natural Science Foundation of China
Recommended Citation
Liu, Cong; Duan, Hua; Zeng, Qing Tian; Zhou, Meng Chu; Lu, Faming; and Cheng, Jiujun, "Towards comprehensive support for privacy preservation cross-organization business process mining" (2019). Faculty Publications. 7505.
https://digitalcommons.njit.edu/fac_pubs/7505