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Context-driven Policies Enforcement for Edge-based IoT Data Sharing-as-a-Service

Abstract

Sharing real-time data originating from connected devices is crucial to real-world intelligent Internet of Things (IoT) applications, i.e., based on artificial intelligence/machine learning (AI/ML). Such IoT data sharing involves multiple parties for different purposes and is usually based on data contracts that might depend on the dynamic change of IoT data variety and velocity. It is still an open challenge to support multiple parties (aka tenants) with these dynamic contracts based on the data value for their specific contextual purposes.This work addresses these challenges by introducing a novel dynamic context-based policy enforcement framework to support IoT data sharing (on-Edge) based on dynamic contracts. Our enforcement framework allows IoT Data Hub owners to define extensible rules and metrics to govern the tenants in accessing the shared data on the Edge based on policies defined with static and dynamic contexts. We have developed a proof-of-concept prototype for sharing sensitive data such as surveillance camera videos to illustrate our proposed framework. The experimental results demonstrated that our framework could soundly and timely enforce context-based policies at runtime with moderate overhead. Moreover, the context and policy changes are correctly reflected in the system in nearly real-time.
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Category

Academic chapter

Language

English

Author(s)

  • Huu-Ha Nguyen
  • Phu H. Phung
  • Phu Nguyen
  • Hong-Linh Truong

Affiliation

  • SINTEF Digital / Sustainable Communication Technologies
  • Aalto University
  • University of Dayton

Year

2022

Publisher

IEEE (Institute of Electrical and Electronics Engineers)

Book

Proceedings of 2022 IEEE International Conference On Services Computing (SCC)

ISBN

9781665481465

Page(s)

221 - 230

View this publication at Norwegian Research Information Repository