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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. 

Increasing number of internet connected devices has paved a path for smarter ecosystems in various sectors such as agriculture, aquaculture, manufacturing, healthcare, etc. Especially, integrating technologies like big data, artificial intelligence (AI), blockchain, etc. with internet connected devices has increased efficiency and productivity. Therefore, fishery farmers have started adopting smart fisheries technologies to better manage their fish farms. Despite their technological advancements smart fisheries are exposed and vulnerable to cyber-attacks that would cause a negative impact on the ecosystem both physically and economically. Therefore in this paper, we present a smart fisheries ecosystem where the architecture describes various interactions that happen between internet connected devices. We develop a smart fisheries ontology based on the architecture and implement Attribute Based Access Control System (ABAC) where access to resources of smart fisheries is granted by evaluating the requests. We also discuss how access control decisions are made in multiple use case scenarios of a smart fisheries ecosystem. Furthermore, we elaborate on some AI applications that would enhance the smart fisheries ecosystem.