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A Secure Remote Monitoring Framework Supporting Efficient Fine-Grained Access Control and Data Processing in IoT

  • Yaxing ChenEmail author
  • Wenhai Sun
  • Ning Zhang
  • Qinghua Zheng
  • Wenjing Lou
  • Y. Thomas Hou
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 254)

Abstract

As an important application of the Internet-of-Things, many remote monitoring systems adopt a device-to-cloud network paradigm. In a remote patient monitoring (RPM) case, various resource-constrained devices are used to measure the health conditions of a target patient in a distant non-clinical environment and the collected data are sent to the cloud backend of an authorized health care provider (HCP) for processing and decision making. As the measurements involve private patient information, access control, confidentiality, and trustworthy processing of the data become very important. Software-based solutions that adopt advanced cryptographic tools, such as attribute-based encryption and fully homomorphic encryption, can address the problem, but they also impose substantial computation overhead on both patient and HCP sides. In this work, we deviate from the conventional software-based solutions and propose a secure and efficient remote monitoring framework using latest hardware-based trustworthy computing technology, such as Intel SGX. In addition, we present a robust and lightweight “heartbeat” protocol to handle notoriously difficulty user revocation problem. We implement a prototype of the framework for PRM and show that the proposed framework can protect user data privacy against unauthorized parties, with minimum performance cost compared to existing software-based solutions with such strong privacy protection.

Keywords

Remote patient monitoring Internet-of-Things (IoT) Fine-grained access control Secure hardware Trusted computing 

Notes

Acknowledgement

This work was sponsored by National Key Research and Development Program of China under Grant No. 2016YFB1000303, Innovative Research Group of the National Natural Science Foundation of China (61721002), Innovation Research Team of Ministry of Education (IRT_17R86), the National Science Foundation of China under Grant Nos. 61502379, 61532015 and 61672420, Project of China Knowledge Center for Engineering Science and Technology, and China Scholarship Council under Grant No. 201606280105. This work was also supported in part by US National Science Foundation under grants CNS-1446478 and CNS-1443889.

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Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2018

Authors and Affiliations

  • Yaxing Chen
    • 1
    • 2
    Email author
  • Wenhai Sun
    • 2
  • Ning Zhang
    • 2
  • Qinghua Zheng
    • 1
  • Wenjing Lou
    • 2
  • Y. Thomas Hou
    • 2
  1. 1.School of Electronic and Information EngineeringXi’an Jiaotong UniversityXi’anChina
  2. 2.Department of Computer ScienceVirginia Polytechnic Institute and State UniversityBlacksburgUSA

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