DE-IDENTIFICATION TECHNIQUE FOR IOT WIRELESS SENSOR NETWORK PRIVACY PROTECTION
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: Yennun Huang,
Szu-Chuang Li, Bo-Chen Tai, Chieh-Ming Chang, Dmitrii I. Kaplun, Denis N.
Butusov
Journal Code: jptkomputergg170009
