DE-IDENTIFICATION TECHNIQUE FOR IOT WIRELESS SENSOR NETWORK PRIVACY PROTECTION

  • Yennun Huang
  • Szu-Chuang Li
  • Bo-Chen Tai
  • Chieh-Ming Chang
  • Dmitrii I. Kaplun Saint Petersburg Electrotechnical University
  • Denis N. Butusov Saint Petersburg Electrotechnical University
Keywords: differential privacy, Internet of Things, sensor network

Abstract

As the IoT ecosystem becoming more and more mature, hardware and software vendors are trying create new value by connecting all kinds of devices together via IoT. IoT devices are usually equipped with sensors to collect data, and the data collected are transmitted over the air via different kinds of wireless connection. To extract the value of the data collected, the data owner may choose to seek for third-party help on data analysis, or even of the data to the public for more insight. In this scenario it is important to protect the released data from privacy leakage. Here we propose that differential privacy, as a de-identification technique, can be a useful approach to add privacy protection to the data released, as well as to prevent the collected from intercepted and decoded during over-the-air transmission. A way to increase the accuracy of the count queries performed on the edge cases in a synthetic database is also presented in this research.

Author Biographies

Yennun Huang

Distinguished Researcer Fellow

CITI, Academia Sinica

Szu-Chuang Li

Postdoc Research Fellow

CITI, Academia Sinica

Bo-Chen Tai

Postdoc Research Fellow

CITI, Academia Sinica

Chieh-Ming Chang

Research Assistant

CITI, Academia Sinica

Published
2017-02-28