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A secured data management scheme for smart societies in industrial internet of things environment

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dc.contributor.author Babar, Muhammad
dc.contributor.author Khan, Fazlullah
dc.contributor.author Iqbal, Waseem
dc.contributor.author Yahya, Abid
dc.contributor.author Arif, Fahim
dc.contributor.author Tan, Zhiyuan
dc.contributor.author Chuma, Joseph
dc.date.accessioned 2019-03-21T07:33:39Z
dc.date.available 2019-03-21T07:33:39Z
dc.date.issued 2018-07
dc.identifier.citation Babar, Muhammad, et al (2018) A secured data management scheme for smart societies in industrial internet of things environment. IEEE Access 6:1-1 en_US
dc.identifier.issn 2169-3536
dc.identifier.uri https://repository.biust.ac.bw/handle/123456789/73
dc.description.abstract Smart societies have an increasing demand for quality-oriented services and infrastructure in an industrial Internet of Things (IIoT) paradigm. Smart urbanization faces numerous challenges. Among them, secured energy demand-side management (DSM) is of particular concern. The IIoT renders the industrial systems to malware, cyberattacks, and other security risks. The IIoT with the amalgamation of big data analytics can provide ef cient solutions to such challenges. This paper proposes a secured and trusted multilayered DSM engine for a smart social society using IIoT-based big data analytics. The major objective is to provide a generic secured solution for smart societies in IIoT environment. The proposed engine uses a centralized approach to achieve optimum DSM over a home area network. To enhance the security of this engine, a payload-based authentication scheme is utilized that relies on a lightweight handshake mechanism. Our proposed method utilizes the lightweight features of the constrained application protocol to facilitate the clients in monitoring various resources residing over the server in an energy-ef cient manner. In addition, data streams are processed using big data analytics with MapReduce parallel processing. The proposed authentication approach is evaluated using NetDuino Plus 2 boards that yield a lower connection overhead, memory consumption, response time, and a robust defense against various malicious attacks. On the other hand, our data processing approach is tested on reliable datasets using Apache Hadoop with Apache Spark to verify the proposed DMS engine. The test results reveal that the proposed architecture offers valuable insights into the smart social societies in the context of IIoT. en_US
dc.language.iso en en_US
dc.publisher IEEE Explore en_US
dc.subject Demand side management en_US
dc.subject Home area network en_US
dc.subject Industrial internet of things en_US
dc.subject Security en_US
dc.subject Smart societies en_US
dc.title A secured data management scheme for smart societies in industrial internet of things environment en_US
dc.description.level phd en_US
dc.description.accessibility unrestricted en_US
dc.description.department cte en_US


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