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

• Main Authors: Nataliia Neshenko, Christelle Nader, Elias Bou-Harb, Borko Furht
• Format: Article
• Language: English
• Published: SpringerOpen 2020-10-01
• Series: Journal of Big Data
• Subjects: Cyber analytics; Decision support models; Data science; Knowledge discovery; Machine learning; Applied analytics
• Online Access: http://link.springer.com/article/10.1186/s40537-020-00363-0

Abstract 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.