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

Nataliia Neshenko,Borko Furht,Christelle Nader,Elias Bou-Harb

doi:10.1186/s40537-020-00363-0

Nataliia Neshenko, Borko Furht + Show 2 more

Open Access

https://doi.org/10.1186/s40537-020-00363-0

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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.

Highlights

The United Nations predicts that two-thirds of the world population will live in urban areas [1] by 2050; implying that around 1.5 million people around the globe will move into a city every week [2]
In this article, we presented a literature survey of methods that support the visibility of cyber threats in the context of smart cities
We described and evaluated the methods dedicated to modeling dependencies among various infrastructure of smart cities, risk assessment methods, and attack detection techniques

Summary

Introduction

The United Nations predicts that two-thirds of the world population will live in urban areas [1] by 2050; implying that around 1.5 million people around the globe will move into a city every week [2]. Cities use sensors to detect pipe leaks; New York city saved more than $73 million in water costs by notifying residents about possible (predicted) water leaks [4]. The latter becomes possible after the deployment of smart water meters and by exploiting advanced data analysis algorithms.

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Conclusion