Abstract
Smart cities are increasingly facing cyber-attacks due to the endeavors they have made in technological advancements. The challenge for smart cities, that utilize complex digital networks to manage city systems and services, is that any device that relies on internet connectivity to function is a potential cyber-attack victim. Smart cities use smart sensors. Online Social Networks (OSNs) act as human sensors offering significant contributions to the amount of data used in smart cities. OSNs can also be used as a coordination and amplification platform for attacks. For instance, aggressors can increase the impact of an attack by causing panic in an area by promoting attacks using OSNs. Public data can help aggressors to determine the best timing for attacks, scheduling attacks, and then using OSNs to coordinate attacks on smart city infrastructure. This convergence of the cyber and physical worlds is known as cybernetics. Quantitative socio-technical methods such as deviant cyber flash mob detection (DCFM) and focal structure analysis (FSA) can provide reconnaissance capabilities that enable cities to look beyond internal data and identify threats based on active events. Assessment of powerful actors using DCFM detection methods can help to identify and prevent attacks. Groups of powerful hackers can be identified through FSA which is a model that uses a degree centrality method at the node-level and spectral modularity at group-level to measure the power of a focal structure (a subset of the network). DCFM and FSA models can help cyber-security experts by providing a better picture of the threat which will help to plan a better response.