Особенности оценки вредоносной активности в инфраструктуре умного города на основе грануляции информации и нечетко-гранулярных вычислений

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.

Publication Details

Journal
Репозиторий БГУИР (BSUIR Repository)
Published
2025-01-01
Primary Topic
Smart Cities and Technologies
Type
article
Field-Weighted Citation Impact
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article

Особенности оценки вредоносной активности в инфраструктуре умного города на основе грануляции информации и нечетко-гранулярных вычислений

Репозиторий БГУИР (BSUIR Repository)
Smart Cities and Technologies
article

Особенности оценки вредоносной активности в инфраструктуре умного города на основе грануляции информации и нечетко-гранулярных вычислений

article en

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.

Репозиторий БГУИР (BSUIR Repository)
Sustainable cities and communities
Openalex Percentile: Top 40%
Smart Cities and Technologies
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