BAE Systems to advance IARPA's machine learning for data security assurance
Image courtesy BAE Systems
BAE Systems will advance machine learning and artificial intelligence technology and techniques to identify signals in the RF spectrum under the terms of the contract, which is part of the Securing Compartmented Information with Smart Radio Systems (SCISRS) programme.
The technology will provide enhanced situational awareness, help to target threats and secure communications against malicious attacks.
“In uncontrolled environments, secure communications can be jeopardised by RF signals that are almost impossible to manually find and identify in real time,” said Scott Kuzdeba, chief scientist for BAE Systems’ FAST Labs research and development organisation. “Our technology will identify RF signals in increasingly crowded electromagnetic spectrum environments, providing commercial or military users with greater automated situational awareness of their operating environment.”
Intelligence Community and Department of Defense missions require that information and data be securely generated, stored, used, transmitted and received. This needs to be the case even when originating in unsecured and uncontrolled environments.
The goal of the SCISRS programme is to develop smart radio techniques to automatically understand these environments in order to enable securing data, including detecting and characterising complex RF anomalies and unexpected signals. The specific types of anomalies include hidden, altered, or mimicked signals and abnormal unintended emissions.
The programme - which includes collaboration with subcontractors PFP Cybersecurity, Intelligent Automation (a BlueHalo Company), Signal Processing Technologies and Virginia Polytechnic Institute and State University - will leverage BAE Systems’ autonomy portfolio and build on the company’s work on DARPA’s Radio Frequency Machine Learning System (RFMLS) programme.
