Do you have full control of your ‘smart’ home?
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Abstract
Smart home devices are gaining huge popularity as they redefine how we entertain, keep a heathy life style or educate our
children. They promise to improve our life quality, energy-efficiency and home security. However, at the same time, we understand
so little about these fast emerging technologies and pay even less attention on how they achieve these efficiencies without
compromising our personal privacy and security.
Although studies have identified security risks related to some
high profile smart home devices, such as the risks of being hacked into for theft or blackmailing, we have much less understanding
about privacy risks associated with the use of smart home devices. Have our personal conversations been transmitted to data
centres to improve their voice recognition algorithms without our knowing? Has our daily routing been made accessible to our
home insurance companies which will compromise our credit? Have our energy consumption details been shared with leading companies
who will provide targeted products for us at a higher price? Even less we know whether we would face a higher privacy risks
if the sharing of these personal information became coordinated among different manufactures or the data centres behind them.
As consumers of smart home devices, are we gaining benefits without losing control to our private lives, or are we buying
ourselves into bigger privacy intrusion?
The goal of this project is to achieve a fuller understanding about
the range of privacy risks associated with smart home devices and their accompanying apps. This will benefit both potential
consumers and smart home developers. This project will survey the different types of personal data being collected by different
smart-home devices in the market, by surveying related literature and deploying some hands-on experiments.
The
outcome of the project will include 1) a framework for categorising the types of personal data that are made accessible by
market leading devices as well as new devices in the store; 2) a data model to capture the sharing of personal data in a typical
smart-home environment, ranging from who (manufacturers or devices) made which data accessible, where, at what time; 3) a
visualisation prototype of the personal data landscape in a typical smart home setting; 4) understandings about the effectiveness
of these information on consumers’ decision making of smart home devices through a small user study; and 5) a reflection
on the privacy risks associated with smart-home devices.
Reference points: http://ieeexplore.ieee.org/document/7546527/
Prerequisite: to have some security knowledge