This webinar presents modern deep learning (DL) techniques for radio frequency (RF) imagery and signals (i.e., Synthetic Aperture Radar/SAR data, communication signals) classification. First, Dr. Majumder provides a short overview of machine learning (ML) /DL theory and an understanding of SAR imagery and RF signals. Then he demonstrates detailed algorithmic implementation and performance of DL algorithms on classifying SAR data and RF signals. Dr. Majumder presents recent research results, technical challenges, and directions of DL-based object classification for RF sensing. Finally, he covers adversarial attacks and mitigation techniques involving DL-based RF object recognition.
CSIAC offers free webinars on a regular basis with experts in the technical subject areas of Cybersecurity, Software Engineering, Modeling & Simulation, and Knowledge Management/Information Sharing.
The objective of the DoD's Digital Engineering Strategy, released in June 2018, is to promote the use of models to digitally represent systems and components along with digital artifacts as a technical means of communication across a diverse set of stakeholders. The strategy addresses a range of disciplines involved in the acquisition and procurement of national defense systems. It encourages innovation in modernizing the way we build, test, field, and sustain our national defense systems and how we train and shape the workforce to use these practices.
Future military conflicts will take place in contested environments where remote sensors deployed in the field will employ advanced artificial intelligence and machine learning technology to reason about the battlespace in the absence of connectivity to manned ground stations. The Air Force Research Laboratory has developed Agile Condor, a flexible airborne testbed used to demonstrate and validate advanced high-performance computing hardware and software configurations. This webinar will discuss Agile Condor’s successful demonstration of state-of-the-art machine learning (ML) software. The embedded ML software algorithms successfully implemented “supercomputing at the edge” through the detection and classification of several ground-based objects and signals.
Established in 2016 by the Secretary of Defense, and born out of Hack The Pentagon, the Vulnerability Disclosure Program (VDP) operates to strengthen the security of the Department of Defense (DoD) Information Network (DoDIN) by crowdsourcing the discovery of cyber-based vulnerabilities.
Cyber monitoring: you cannot monitor what you cannot measure. In the world of computer communications, monitoring takes on two distinct forms: performance measuring and monitoring physical parameters, and security monitoring of network traffic and computer processes.
Over the past several years, FDA has undertaken a significant and diverse set of efforts aimed at improving not only medical device cybersecurity, but cybersecurity across the healthcare sector. The agency has worked internally on efforts such as updated guidance with respect to satisfying regulatory requirements for cybersecurity within medical devices, the development of a playbook related to regional response, “boot camps” for threat modeling, and others. FDA has also supported the development of vulnerability scoring system specifically targeted at medical devices.
This presentation will share the vision of software bill of materials (SBOM) from an international open process that brought together open source, commercial software developers, the embedded systems and ICS community, and enterprise customers, demonstrating the value of supply chain transparency at each step of the supply chain. It will cover the basics of SBOM, how you can begin implementing it today, and what we might expect in the coming years for software supply chain and software assurance.
Threat intelligence, coupled with the latest advancements in intelligent and self-protecting data technology, provides visibility into the latest threats, which can help you avoid becoming a backdoor in the next big data breach.
This webinar covers important building blocks to establish, maintain, and manage a threat intelligence program at your organization.
In this webinar, Professor James Giordano of Georgetown University describes the uses and value of big data and cyber-capabilities in bioscience and biotechnology; addresses the national security, intelligence, and defense applications of these tools and methods; illustrates vulnerabilities in these systems' infrastructures and functions, and posits the importance and necessity of bio-cybersecurity as a multi-organizational posture and enterprise.
This webinar provides an overview of Adversarial Machine Learning (AML), its relationship to Generative (Deep) Learning, and ways to view AML as a potential enabler for deploying more comprehensive system-level Machine Learning capabilities. The basic ideas driving AML and the system-level architecture needs of an effective integrated ML capability are compared to find areas of commonality and future utility beyond single-shot, algorithm-by-algorithm approaches to AML and remediation techniques.