Cybersecurity Risk Assessment in Smart City Infrastructures

Abstract

The article is devoted to cybersecurity risk assessment of the dynamic device-to-device networks of a smart city. Analysis of the modern security threats at the IoT/IIoT, VANET, and WSN inter-device infrastructures demonstrates that the main concern is a set of network security threats targeted at the functional sustainability of smart urban infrastructure, the most common use case of smart networks. As a result of our study, systematization of the existing cybersecurity risk assessment methods has been provided. Expert-based risk assessment and active human participation cannot be provided for the huge, complex, and permanently changing digital environment of the smart city. The methods of scenario analysis and functional analysis are specific to industrial risk management and are hardly adaptable to solving cybersecurity tasks. The statistical risk evaluation methods force us to collect statistical data for the calculation of the security indicators for the self-organizing networks, and the accuracy of this method depends on the number of calculating iterations. In our work, we have proposed a new approach for cybersecurity risk management based on object typing, data mining, and quantitative risk assessment for the smart city infrastructure. The experimental study has shown us that the artificial neural network allows us to automatically, unambiguously, and reasonably assess the cyber risk for various object types in the dynamic digital infrastructures of the smart city.

Perception of the Quality of Smart City Solutions as a Sense of Residents’ Safety

“…In Table 4 there are functions that an enterprise must have, they are marked with the letter M. The lack of such features means that customers go somewhere to the competition [75]. It can be concluded that the respondents understand the need for sustainable development [76], and the so-called the related features were treated by them mainly as indispensable features, i.e., they must be among the attributes of corporate social media [77,78]. Comparing the results of these studies with previous studies available in the literature, it was possible.…”

“…In the case of smart city activities, individual dimensions of activities have specific advantages and disadvantages. Smart solutions provide long-term benefits, ensure a balance between the availability of modern intelligent solutions and the sense of security among residents, the sense of privacy and freedom cannot be disturbed [78][79][80][81].…”

Dinamička Procena Bezbednosnog Rizika U Industrijskim Iot Sistemima

“…Iz tog razloga uvedena je mera povrata investicija u bezbednost (Return on Security Investment, ROSI) za kvantifikaciju gubitaka koji su izbegnuti zahvaljujući preventivnim ulaganjima u bezbednost [11]. Kvantitativni metodi za procenu rizika mogu se klasifikovati u tri osnovne kategorije: (1) analitički metodi kao što su: analiza osetljivosti, analiza scenarija, metod diskontnih stopa prilagođenih riziku; (2) probabilistički teorijski metodi koji se zasnivaju na simulaciji, teoriji igara ili konstrukciji stabla, i (3) nekonvencionalni metodi, među kojima su najpoznatiji metodi zasnovani na fazi logici ili na mašinskom učenju [12]. Hibridni metodi kombinuju prethodno opisane pristupe, na primer, stručnu procenu sa nekim od kvantitativnih metoda [13], [14].…”

“…U [28] je prikazan pristup za dinamičku procenu bezbednosnog rizika u ICS, zasnovan na Bajesovoj mreži sa fazi verovatnoćama, koji je verifikovan na primeru simulacije upravljanja hemijskim reaktorom. Kvantitativni metod za procenu sajber bezbednosnog rizika u infrastrukturi pametnih gradova, zasnovan na ANN pristupu, opisan je u [12].…”

Digital Technologies for Urban Metabolism Efficiency: Lessons from Urban Agenda Partnership on Circular Economy

“…On the other hand, the strategy of digitizing the circularity of urban metabolism through real-time monitoring stations of water and energy consumption, GPS tracking sensors and digital cameras to control and manage mobility, cloud computing platforms for sharing sensitive data and information between agencies, departments, divisions, utilities, etc., outlines a multitude of challenges and criticalities related to: (a) the quality of the data used [75]; (b) the degree of traditional and cyber security [76]; (c) the necessary integration of data and information of different types, provided by a wide range of stakeholders [77], and (d) the ability of policymakers, urban managers and planners to convert continuous and real-time feedback from stakeholders into forward-looking urban circularity strategies [11].…”