Abstract:

IoT for Defense and National Security covers topics on IoT security, architecture, robotics, sensing, policy, operations, and more, presenting the latest results from the U.S. Army’s Internet of Battle Things and the U.S. Defense Department’s premier IoT research initiative. The presentation discusses organizational challenges in converting defense industrial operations to IoT and summarizes policy challenges and recommendations for controlling government use of IoT in free societies. As a modern reference, this presentation covers multiple technologies in IoT solution deployment that include KepServerEX for edge connectivity to industrial protocols, AWS IoT Core for IoT data processing, Amazon S3 for scalable storage of IoT Data, and more. To aid in reader comprehension, the text uses case studies illustrating the challenges and solutions for using robotic devices in defense applications, plus case studies on using IoT for a defense industrial base. Content developed by leading researchers and practitioners of IoT technology for defense and national security, IoT for Defense and National Security also includes information on:

• IoT resource allocation via mixed discrete/continuous optimization (monitoring existing resources and reallocating them in response to adversarial actions)
• principles of robust learning and inference for Internet of Battlefield Things (IoBTs), covering methodologies to make machine learning models provably robust
• AI-enabled processing of environmental sounds in commercial and defense environments, such as detecting faults in industrial manufacturing
• vulnerabilities in tactical IoT systems that come about due to the intrinsic nature of building networks using several devices and components

For application engineers from security and defense-related companies and professors and students in military courses, IoT for Defense and National Security is a one-of-a-kind resource of the topic, providing expansive coverage of an important yet sensitive topic that is often shielded from the public due to classified or restricted distributions.