A Review on Temporal Knowledge Graph Completion in the Context of Internet of Things and Industrial Security
Runze Li, Banglie Yang, Shuo Zhu, Sha Xiang
Communications in computer and information science
Problems Identified (5)
Static KG temporal inadequacy: Traditional static knowledge graphs are inadequate for representing evolving threats and real-time security events in industrial IoT security.
Sparse and incomplete threat data: Sparse threat intelligence and incomplete event data make it necessary to predict missing or future security knowledge.
IoT industrial security TKGC challenges: IoT and industrial security settings present distinct challenges for applying temporal knowledge graph completion.
Static KG temporal inadequacy: Traditional static knowledge graphs are inadequate for representing evolving threats and real-time security events in industrial IoT security.
Sparse and incomplete threat data: Sparse threat intelligence and incomplete event data make it necessary to predict missing or future security knowledge.
Proposed Solutions (5)
Temporal knowledge graphs: Temporal knowledge graphs model time-dependent relations and entities to represent dynamic security incidents.
Temporal knowledge graph completion: Temporal knowledge graph completion techniques are used to predict potential threats and update security knowledge bases in real time.
TKGC survey and taxonomy: The paper reviews TKGC approaches and categorizes them into interpolation-based and extrapolation-based methods.
Temporal knowledge graphs: Temporal knowledge graphs model time-dependent relations and entities to represent dynamic security incidents.
Temporal knowledge graph completion: Temporal knowledge graph completion techniques are used to predict potential threats and update security knowledge bases in real time.
Results (3)
TKGC approach taxonomy:
Advancement analysis:
Future directions for IoT security TKGC:
Research Domain
Temporal knowledge graph completion for IoT and industrial security