A Balancing of Privacy Protection and Personalized Service in Big Data - Application of Thinking Process and TRIZ"s Principles -
Jaejung Kang · The Journal of Internet Electronic Commerce Resarch · 2018
For providing customized personal services, it is necessary to collect a large amount of personal information, and while for protecting privacy, the collection and storage of personal information should be minimized. This study proposes various measures to balance the privacy protection and personalized service in era of big data by applying separation principles of TRIZ and Thinking Process of TOC(Theory of Constraint). First, as a spatial separation solution, we suggested some methods by using physically and logically separating approaches for protecting personal identified information. Second, temporal separation methods are to apply different measures according to the data lifecycle of personal information, such as data collection, processing, delivery and use. Third, contextural separation measure can be applied differently according to the contextural attributes, such as data analysis purpose, size of the data to be managed, and personal information type etc. Fourth, it is a method of separating by whole and part which is a searching process for better solutions by distinguishing between general areas and specific areas for protection of privacy. These approaches are expected to be used to search and prepare the policies and rules for balancing customized service and privacy protection in Big Data Era.