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Dynamic Task Scheduler for Real Time Requirement in Cloud Computing System Read chapter Read first chapter

2018 | OriginalPaper | Chapter

IoT-SDNPP: A Method for Privacy-Preserving in Smart City with Software Defined Networking

Authors : Mehdi Gheisari, Guojun Wang, Shuhong Chen, Hamidreza Ghorbani

Published in: Algorithms and Architectures for Parallel Processing

Publisher: Springer International Publishing

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Abstract

Internet of Things (IoT) era appeared to connect all the digital and non-digital devices around the globe through the Internet. Based on predictions, billions of devices will be connected with each other by 2050 with the aim of providing high-level and humanized services. One application of IoT is a smart city that means IT-enabled cities running by themselves without human interventions. These large number of devices, especially in a smart city environment, may sense sensitive and personal data which makes the system vulnerable. We have to protect private information so that unwanted parties would not be able to find original data, which is a part of privacy-preserving. Meanwhile, a new networking paradigm evolved called Software Defined Networking (SDN) that aimed to separate the Control Plane and the Data Plane of the network results in much more flexibility to manage the network. Most of the existing works are deficient in flexibility or very tedious. In this paper, we facilitated IoT-based smart city with SDN paradigm to leverage the benefits of SDN. Then, based on the environment, we propose IoT-SDN Privacy-Preserving, IoT-SDNPP, to keep private data safe. We have done extensive experiments, and the experimental results have demonstrated the effectiveness of our approach.

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Metadata
Title
IoT-SDNPP: A Method for Privacy-Preserving in Smart City with Software Defined Networking
Authors
Mehdi Gheisari
Guojun Wang
Shuhong Chen
Hamidreza Ghorbani
Copyright Year
2018
Book
Algorithms and Architectures for Parallel Processing

Print ISBN: 978-3-030-05062-7

Electronic ISBN: 978-3-030-05063-4

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-030-05063-4_24

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