A survey of methods supporting cyber situational awareness in the context of smart cities

被引:0
作者
Nataliia Neshenko
Christelle Nader
Elias Bou-Harb
Borko Furht
机构
[1] Florida Atlantic University,Department of Computer and Electrical Engineering and Computer Sciences
[2] University of Texas at San Antonio,The Cyber Center For Security and Analytics
来源
Journal of Big Data | / 7卷
关键词
Cyber analytics; Decision support models; Data science; Knowledge discovery; Machine learning; Applied analytics; Decision-making; Smart cities; Internet of things;
D O I
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学科分类号
摘要
A modern urban infrastructure no longer operates in isolation, but instead, leverages the latest technologies to collect, process, and distribute aggregated knowledge in order to improve the quality of the provided services and promote the efficiency of resource consumption. This technological development, however, manifests in the form of new vulnerabilities and a plethora of attack vectors. In the same context, the ambiguity of ever-evolving cyber threats and their debilitating consequences introduce new barriers for decision-makers. Therefore, cyber situational awareness of smart cities emerges as a mission-critical task that requires support methods for effective and timely decision-making. In this article, we investigate the threat landscape of smart cities, survey and reveal the progress in data-driven methods for situational awareness and evaluate their effectiveness when addressing various cyber threats. We draw several potential research directions that aim at advancing cyber situational awareness in the context of smart cities.
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