Distributed single-dimensional time series data real-time privacy protection publishing method with consistency

Abstract

The invention discloses a distributed single-dimensional time series data real-time privacy protection publishing method with consistency, and belongs to the field of privacy protection. According tothe method, the sampling frequency is adjusted through a self-adaptive sampling strategy, sampling data are disturbed through a Laplace mechanism at the sampling moment, then distributed posteriori estimation is conducted on published data of all nodes at the sampling moment through a single-dimensional perception information correction strategy based on Kalman consistency filtering; at the non-sampling moment, the priori prediction data is directly published, and finally, the distributed single-dimensional time sequence perception data real-time publishing method which does not depend on a central server and has differential privacy guarantee and consistency is achieved, and the real-time requirement of dynamic data publishing and the consistency requirement of distributed data publishingare met. The invention has a good application effect in an actual data scene, and can be applied to distributed dynamic perception data release systems such as a smart grid distributed power consumption load monitoring system and a disease monitoring application system.

Description

Technical field[0001]The invention belongs to the field of privacy protection, and specifically relates to a distributed single-dimensional time series data real-time privacy protection publishing method with consistency.Background technique[0002]With the rapid development of the Internet of Things technology and the continuous improvement of the hardware level, people’s production and life are becoming more and more digital, intelligent and networked. All kinds of smart devices are flooding people’s daily life, and they always perceive people’s own and Data closely related to the surrounding environment. The aggregation, release, mining and analysis of a large number of users' perception data can provide a full range of information and knowledge, and provide people with more professional and personalized services. For example, gathering and publishing information such as user browsing, shopping records, and book image ratings can be used to formulate more convenient and preferentia...

AI Technical Summary

Problems solved by technology

[0005] Aiming at the issue of privacy-preserving release of distributed time-series-aware data, existing research cannot effectively solve the consistency requirements in the process of dynamic release of distributed data while improving the utility of continuous release data

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