A Privacy-Preserving Data Inference Framework for Internet of Health Things Networks

by   James Jin Kang, et al.

Privacy protection in electronic healthcare applications is an important consideration due to the sensitive nature of personal health data. Internet of Health Things (IoHT) networks have privacy requirements within a healthcare setting. However, these networks have unique challenges and security requirements (integrity, authentication, privacy and availability) must also be balanced with the need to maintain efficiency in order to conserve battery power, which can be a significant limitation in IoHT devices and networks. Data are usually transferred without undergoing filtering or optimization, and this traffic can overload sensors and cause rapid battery consumption when interacting with IoHT networks. This consequently poses restrictions on the practical implementation of these devices. As a solution to address the issues, this paper proposes a privacy-preserving two-tier data inference framework, this can conserve battery consumption by reducing the data size required to transmit through inferring the sensed data and can also protect the sensitive data from leakage to adversaries. Results from experimental evaluations on privacy show the validity of the proposed scheme as well as significant data savings without compromising the accuracy of the data transmission, which contributes to energy efficiency of IoHT sensor devices.



There are no comments yet.


page 1


Towards Practical Privacy-Preserving Analytics for IoT and Cloud Based Healthcare Systems

Modern healthcare systems now rely on advanced computing methods and tec...

Enhancement of Healthcare Data Performance Metrics using Neural Network Machine Learning Algorithms

Patients are often encouraged to make use of wearable devices for remote...

Thinking Out of the Blocks: Holochain for Distributed Security in IoT Healthcare

The Internet-of-Things (IoT) is an emerging and cognitive technology whi...

Security and Privacy Preserving Data Aggregation in Cloud Computing

Smart metering is an essential feature of smart grids, allowing resident...

Secure Multi-Party Computation based Privacy Preserving Data Analysis in Healthcare IoT Systems

Recently, many innovations have been experienced in healthcare by rapidl...

Anonymity Network Tor and Performance Analysis of ARANEA; an IOT Based Privacy-Preserving Router

There was a time when the word security was only confined to the physica...

No Peeking through My Windows: Conserving Privacy in Personal Drones

The drone technology has been increasingly used by many tech-savvy consu...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.