Signal Knowledge Graph
This addresses the limitations of existing knowledge graphs and reasoning systems for intelligence applications, though it appears incremental as it builds on prior knowledge graph methods.
The paper tackles the problem of reasoning over signals for intelligence purposes by proposing a knowledge graph that models attacker behavior, signal emission, receiver characteristics, and signal summarization to infer underlying causes, using an example of attack inference from combined microphone, camera, and social media data.
This paper presents an knowledge graph to assist in reasoning over signals for intelligence purposes. We highlight limitations of existing knowledge graphs and reasoning systems for this purpose, using inference of an attack using combined data from microphones, cameras and social media as an example. Rather than acting directly on the received signal, our approach considers attacker behaviour, signal emission, receiver characteristics, and how signals are summarised to support inferring the underlying cause of the signal.