A Smart City Infrastructure Ontology for Threats, Cybercrime, and Digital Forensic Investigation

2024-08-04

Forensic Science International: Digital Investigation

AI Summary

Existing digital forensics ontologies (e.g., UCO, CASE) exhibit insufficient semantic coverage, weak cross-domain interoperability, and outdated threat modeling when applied to smart city infrastructure (SCI) scenarios. To address these limitations, this paper proposes the first ontology framework for urban security that unifies the physical, cyber, and social spaces, formalized in OWL 2. It integrates an SCI-specific threat model, attack technique taxonomy, digital forensics workflow, and semantic specifications for evidence chains. Leveraging SPARQL-based reasoning, PROV-O for provenance modeling, and standardized mappings to STIX/TAXII, the ontology enables threat attribution, criminal chain inference, and semantic alignment of evidence chains. The framework supports modeling of 12 representative urban security scenarios, improves inter-departmental forensic collaboration efficiency by 3.2×, and has been validated for compliance with ISO/IEC 27001.

Technology Category

• Knowledge Representation and Reasoning: Ontologies
• Application Domains: Internet of Things, Sensor Networks & Smart Cities
• Data Mining & Knowledge Management: Representing, Reasoning, and Using Provenance, Trust

Application Category

• Security and Privacy: Data transparency and provenance
• Systems and Infrastructure for Web, Mobile and WoT: Web applications in cross-disciplinary domains and verticals such as mixed reality, smart cities, and digital health
• Semantics and Knowledge: Provenance, trust, security and privacy, and ethical issues in managing semantic data

Problem

• Addresses cybercrime in Smart City Infrastructure
• Improves digital forensic investigation tools
• Enhances information sharing and tool interoperability

Innovation

• Expands UCO and CASE ontology
• Implements SCI threat models
• Facilitates collaborative threat identification