Visible to the public Application of Differential Privacy in Location Trajectory Big Data

TitleApplication of Differential Privacy in Location Trajectory Big Data
Publication TypeConference Paper
Year of Publication2020
AuthorsLiu, H., Di, W.
Conference Name2020 International Conference on Intelligent Transportation, Big Data Smart City (ICITBS)
KeywordsAlgorithm, Big Data, big data privacy, Big Data privacy protection, composability, data privacy, data protection, Differential privacy, differential privacy protection, differential privacy protection technology, Global Positioning System, GPS technology, Human Behavior, Internet, location based services, location trajectory, location trajectory Big Data, location trajectory privacy protection, Metrics, mobile computing, mobile Internet technology, position trajectory, pubcrawl, resilience, Resiliency, Scalability, social software

With the development of mobile internet technology, GPS technology and social software have been widely used in people's lives. The problem of big data privacy protection related to location trajectory is becoming more and more serious. The traditional location trajectory privacy protection method requires certain background knowledge and it is difficult to adapt to massive mass. Privacy protection of data. differential privacy protection technology protects privacy by attacking data by randomly perturbing raw data. The method used in this paper is to first sample the position trajectory, form the irregular polygons of the high-frequency access points in the sampling points and position data, calculate the center of gravity of the polygon, and then use the differential privacy protection algorithm to add noise to the center of gravity of the polygon to form a new one. The center of gravity, and the new center of gravity are connected to form a new trajectory. The purpose of protecting the position trajectory is well achieved. It is proved that the differential privacy protection algorithm can effectively protect the position trajectory by adding noise.

Citation Keyliu_application_2020