An AI-based framework for remote sensing supporting multi-domain operations

In today's battlefield, military operations are conducted in all domains including air, land, maritime, space, and cyberspace in addition to the electromagnetic spectrum, and the information environment. The data, network connections, sensors, computer systems and other information technology infrastructures utilized must be protected as adversaries are competing for dominance across all domains. Cyberspace attacks can cause significant disruption to a nation's power grid and other critical infrastructure components resulting in collateral damage and even loss of life. With the continued shortage in Cybersecurity professionals, the government, universities and companies look to Artificial Intelligence Machine Learning (AI/ML) techniques to fill the gap. AI applications have been successfully applied to Department of Defense (DoD) to detect and mitigate cyber-attacks. Moreover, cybercriminals, state actors and other adversaries have used AI to plan and launch cyber-attacks. The Army Research Laboratory is working to employ AI services using a novel framework that proactively detects and responds to attacks on a remote sensor network. The components of the framework include AI/ML for detecting malware and intrusion detection and prevention (IDP), cloud AI tools for sensor and system monitoring, log monitoring for detection of user behavior anomalies and sensor resiliency characteristics, and a visual mapping application to display sensor and target locations supporting geographically and social distancing of observers and parties of interest. Notifications are part of the framework to ensure system administrators are made aware of possible threats in near real-time. This paper provides a detailed description of components of this framework and the initial use-case for a small distributed remote sensing network application.