A Secured Data Management Scheme for Smart Societies in Industrial Internet of Things Environment

被引:21
作者
Babar, Muhammad [1 ,2 ]
Khan, Fazlullah [3 ]
Iqbal, Waseem [2 ]
Yahya, Abid [4 ]
Arif, Fahim [2 ]
Tan, Zhiyuan [5 ]
Chuma, Joseph M. [4 ]
机构
[1] Iqra Univ, Dept Comp & Technol, Islamabad 44000, Pakistan
[2] Natl Univ Sci & Technol, Comp Software Engn Dept, Islamabad 44000, Pakistan
[3] Abdul Wali Khan Univ, Comp Sci Dept, Mardan 23200, Pakistan
[4] Botswana Int Univ Sci & Technol, Fac Engn & Technol, Dept Elect Comp & Telecommun, Palapye 016, Botswana
[5] Edinburgh Napier Univ, Sch Comp, Edinburgh EH10 5DT, Midlothian, Scotland
关键词
Demand side management; home area network; industrial Internet of Things; security; smart societies; trust; DEMAND-SIDE MANAGEMENT; AUTHENTICATION; URBANIZATION; CHALLENGES;
D O I
10.1109/ACCESS.2018.2861421
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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 efficient 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-efficient 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.
引用
收藏
页码:43088 / 43099
页数:12
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