Improved Mitigation of Cyber Threats in IIoT for Smart Cities: A New-Era Approach and Scheme

Abstract

Cybersecurity in Industrial Internet of Things (IIoT) has become critical as smart cities are becoming increasingly linked to industrial control systems (ICSs) used in critical infrastructure. Consequently, data-driven security systems for analyzing massive amounts of data generated by smart cities have become essential. A representative method for analyzing large-scale data is the game bot detection approach used in massively multiplayer online role-playing games. We reviewed the literature on bot detection methods to extend the anomaly detection approaches used in bot detection schemes to IIoT fields. Finally, we proposed a process wherein the data envelopment analysis (DEA) model was applied to identify features for efficiently detecting anomalous behavior in smart cities. Experimental results using random forest show that our extracted features based on a game bot can achieve an average F1-score of 0.99903 using 10-fold validation. We confirmed the applicability of the analyzed game-industry methodology to other fields and trained a random forest on the high-efficiency features identified by applying a DEA, obtaining an F1-score of 0.997 using the validation set approach. In this study, an anomaly detection method for analyzing massive smart city data based on a game industry methodology was presented and applied to the ICS dataset.

Smart Cities as Hubs: A Use Case in Public School Buildings

“…Research from the literature on the standards, protocols, and technologies used in the IoT space further highlight the fragmentation of the landscape, which in turns introduces additional difficulties in implementing an effective strategy against cyber attacks [24][25][26][27]. Recent advances in the cyber threat mitigation strategies increasingly make use of statistical and machine learning methods, which rely on access to large datasets and real time information from the IoT layer [28][29][30][31]. The complexity and lack of transparency in the security aspects of Smart City metropolitan-scale deployments raise concerns related to data privacy, particularly for the data that are related to Personal Identifiable Information [32,33].…”

Protocol-Based and Hybrid Access Control for the IoT: Approaches and Research Opportunities

“…Encryption with access control can be used for cloud-based IIoT applications [116][117][118]. Different protocols support M2M communication in IIoT, and hence, protocol-based access control can be used in the hybrid method to improve the efficiency of the access control mechanism [119]. It is crucial when considering the operations over different jurisdictions combining heterogeneous networks.…”