A new security middleware architecture based on fog computing and cloud to support IoT constrained devices

Wissam Razouk, Daniele Sgandurra, Kouichi Sakurai

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Citations (Scopus)

Abstract

The increase of sensitive data in the current Internet of Things (IoT) raises demands of computation, communication and storage capabilities. Indeed, thanks to RFID tags and wireless sensor networks, anything can be part of IoT. As a result, a large amount of data is generated, which is hard for many IoT devices to handle, as many IoT devices are resource-constrained and cannot use the existing standard security protocols. Cloud computing might seem like a convenient solution, since it offers on-demand access to a shared pool of resources such as processors, storage, applications and services. However this comes as a cost, as unnecessary communications not only burden the core network, but also the data center in the cloud. Therefore, considering suitable approaches such as fog computing and security middleware solutions is crucial. In this paper, we propose a novel middleware architecture to solve the above issues, and discuss the generic concept of using fog computing along with cloud in order to achieve a higher security level. Our security middleware acts as a smart gateway as it is meant to pre-process data at the edge of the network. Depending on the received information, data might either be processed and stored locally on fog or sent to the cloud for further processing. Moreover, in our scheme, IoT constrained devices communicate through the proposed middleware, which provide access to more computing power and enhanced capability to perform secure communications. We discuss these concepts in detail, and explain how our proposal is effective to cope with some of the most relevant IoT security challenges.

Original languageEnglish
Title of host publicationProceedings of the International Conference on Internet of Things and Machine Learning, IML 2017
EditorsHani Hamdan, Faouzi Hidoussi, Djallel Eddine Boubiche
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450352437
DOIs
Publication statusPublished - Oct 17 2017
Event1st International Conference on Internet of Things and Machine Learning, IML 2017 - Liverpool, United Kingdom
Duration: Oct 17 2017Oct 18 2017

Publication series

NameACM International Conference Proceeding Series

Other

Other1st International Conference on Internet of Things and Machine Learning, IML 2017
CountryUnited Kingdom
CityLiverpool
Period10/17/1710/18/17

All Science Journal Classification (ASJC) codes

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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