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Title A complex network-based approach for security and governance in the smart green city
ID_Doc 44200
Authors Ahmad, A; Ahmad, T; Ahmad, M; Kumar, C; Alenezi, F; Nour, M
Title A complex network-based approach for security and governance in the smart green city
Year 2023
Published
DOI 10.1016/j.eswa.2022.119094
Abstract Interest in smart green cities is growing, and IoT is an underlying driver of this trend. The integration of IoT in smart cities has altered the manner of working and living of society. IoT technologies do, however, come with a number of drawbacks, including vulnerability of highly secure devices, energy consumption, governance, etc. in smart cities. Governance in smart city is more citizen-center and the decisions of government are focused on citizens' demands. Government can identify influential spreaders from this huge voluminous population and take requisite preventive steps such as delaying the spread of rumor, identifying the information source, or blocking the source node. Hence, security of highly vulnerable IoT device and governance are the two main issues of the IoT environment of smart green city. This paper proposes a framework for identifying influential spreaders who play a key role in the governance of smart city as well as determining vulnerable IoT devices that needs to be protected from malware attacks. A framework named as Modified Dynamic Weighted Sum Method, is proposed for determining influential devices and spreaders in smart green cities. The connectivity between devices is considered as a network, then, distinct centrality measures are considered as the multi -attribute of the network, so as to take advantage of each centrality measure. Experiments are conducted on Santender testbed and it was found that static devices play an important role in IoT environment. Hence, they need to be protected from malware attacks. From future perspective, opportunities and challenges in smart city applications are discussed.
Author Keywords Smart green city; Security; Complex network; Governance; Multi-criteria decision making
Index Keywords Index Keywords
Document Type Other
Open Access Open Access
Source Science Citation Index Expanded (SCI-EXPANDED)
EID WOS:000895265800001
WoS Category Computer Science, Artificial Intelligence; Engineering, Electrical & Electronic; Operations Research & Management Science
Research Area Computer Science; Engineering; Operations Research & Management Science
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