CAPD: a context-aware, policy-driven framework for secure and resilient IoBT operations

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https://www.spiedigitallibrary.org/conference-proceedings-of-spie/12113/121130P/CAPD--a-context-aware-policy-driven-framework-for-secure/10.1117/12.2618106.short

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https://doi.org/10.1117/12.2618106
 http://hdl.handle.net/11603/25496

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https://orcid.org/0000-0002-8641-3193
 https://orcid.org/0000-0002-6593-1792

Date

2022-06-06

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conference papers and proceedings
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Citation of Original Publication

Sai Sree Laya Chukkapalli, Anupam Joshi, Tim Finin, and Robert F. Erbacher, "CAPD: a context-aware, policy-driven framework for secure and resilient IoBT operations," Proc. SPIE 12113, Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications IV, 121130P (Presented at SPIE Defense + Commercial Sensing: April 05, 2022; Published: 6 June 2022); https://doi.org/10.1117/12.2618106.

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This work was written as part of one of the author's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law.
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UMBC Ebiquity Research Group

Abstract

The Internet of Battlefield Things (IoBT) will advance the operational effectiveness of infantry units. However, this requires autonomous assets such as sensors, drones, combat equipment, and uncrewed vehicles to collaborate, securely share information, and be resilient to adversary attacks in contested multi-domain operations. CAPD addresses this problem by providing a context-aware, policy-driven framework supporting data and knowledge exchange among autonomous entities in a battlespace. We propose an IoBT ontology that facilitates controlled information sharing to enable semantic interoperability between systems. Its key contributions include providing a knowledge graph with a shared semantic schema, integration with background knowledge, efficient mechanisms for enforcing data consistency and drawing inferences, and supporting attribute-based access control. The sensors in the IoBT provide data that create populated knowledge graphs based on the ontology. This paper describes using CAPD to detect and mitigate adversary actions. CAPD enables situational awareness using reasoning over the sensed data and SPARQL queries. For example, adversaries can cause sensor failure or hijacking and disrupt the tactical networks to degrade video surveillance. In such instances, CAPD uses an ontology-based reasoner to see how alternative approaches can still support the mission. Depending on bandwidth availability, the reasoner initiates the creation of a reduced frame rate grayscale video by active transcoding or transmits only still images. This ability to reason over the mission sensed environment, and attack context permits the autonomous IoBT system to exhibit resilience in contested conditions.