Review on Data Sharing in Smart City Planning Based on Mobile Phone Signaling Big Data: From the Perspective of China Experience: Anonymization VS De-anonymization

Abstract

In the smart city planning based on spatiotemporal big data, the mobile phone signaling big data is the most commonly used data source at the moment. This kind of big data has time and space dimensions and also significant human behavior attributes. According to the relevant Chinese law, the data has been anonymized before sharing, i.e. cannot be identified as a specific individual and cannot be restored again, thus is no longer regarded as personal information. In smart city planning, the mobile phone signaling big data is used to construct the basic dynamic analysis framework of "space-time-behavior". Even if the mobile phone signaling big data has been processed anonymously, it will inevitably show some specific location attribute information of mobile phone users. The anonymous track information can be matched to the corresponding geographical space, so as to mark the active location information of the information subject in a specific period of time. It can easily identify the specific location information such as the job and residence of mobile phone user, and even give user portrait. Existing technology shows that the mobile phone signaling big data is easy to be de-anonymized, and Anonymity rule are not applicable to the sharing of mobile phone signaling big data in the smart city planning. Mobile phone signaling big data belongs to personal sensitive information. Once leaked or abused, it is easy to infringe personal privacy of information subject. Therefore, only using current anonymization means to share the mobile phone signaling big data are not enough to protect the security of personal information in smart city planning, and sharing the mobile phone signaling big data should follow the basic principle of explicit informed consent. In special circumstances or scenarios, breaking through the basic principle of the mobile phone signaling big data sharing should have clear legal provisions and comply with legal procedures.