Paper
28 May 2013 A framework for network-wide semantic event correlation
Author Affiliations +
Abstract
An increasing need for situational awareness within network-deployed Systems Under Test has increased desire for frameworks that facilitate system-wide data correlation and analysis. Massive event streams are generated from heterogeneous sensors which require tedious manual analysis. We present a framework for sensor data integration and event correlation based on Linked Data principles, Semantic Web reasoning technology, complex event processing, and blackboard architectures. Sensor data are encoded as RDF models, then processed by complex event processing agents (which incorporate domain specific reasoners, as well as general purpose Semantic Web reasoning techniques). Agents can publish inferences on shared blackboards and generate new semantic events that are fed back into the system. We present AIS, Inc.’s Cyber Battlefield Training and Effectiveness Environment to demonstrate use of the framework.
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Robert T. Hall and Joshua Taylor "A framework for network-wide semantic event correlation", Proc. SPIE 8757, Cyber Sensing 2013, 875708 (28 May 2013); https://doi.org/10.1117/12.2016126
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CITATIONS
Cited by 1 scholarly publication.
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KEYWORDS
Sensors

Data integration

Data modeling

Artificial intelligence

Data storage

Databases

Analytical research

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