Features of the Assessment of Malicious Activity in Smart City Infrastructure Based on Information Granulation and Fuzzy Granular Calculations

Abstract

The pervasive integration of digital infrastructures within urban environments, while increasing smart city operational efficiencies, has concomitantly engendered intricate security vulnerabilities. Conventional cybersecurity paradigms, predicated on deterministic models, frequently prove inadequate in addressing the dynamic and epistemically uncertain nature of cyber threats. This research introduces a novel methodological framework, leveraging ontology-driven information granulation and knowledge graph-enhanced fuzzy granular computations, to facilitate semantic assessment and mitigation of malicious activities. By transforming raw security telemetry into semantically enriched granules, contextual knowledge extraction is enabled, enhancing inferential efficacy. A case study, employing semantic intrusion detection systems (SIDS) within a simulated ’Smart City’, elucidates the potential of the framework for proactive, knowledge-driven threat detection and semantic response strategies.