Award Data

The information environment has become a new battlefield for adversaries of the United States and its allies. Coordinated campaigns have been waged to radicalize, incite division, inflame, influence elections and public opinion on a variety of issues. These campaigns have weaponized social media by forming networks of synthetic accounts (botnets) which spread mis/disinformation, polarize groups an ...

The United States relies on networks of cyber-physical systems to conduct military and commercial operations, such as logistics, transportation, information sharing, energy production and distribution, financial transactions, elections, and infrastructure management. As the volume and diversity of cyber-attacks on these networks dramatically increase, there is a growing need for advanced tools and ...

BlueRISC's proposed solution takes the form of an automated toolkit that is able to analyze an FPGA bitstream with respect to exploitability. The solution relies on an FPGA-agnostic framework for automatically reverse-engineering an FPGA-bitstream into an intermediate representation (IR). This IR is FPGA agnostic and enables a program-analytic framework for extracting a fundamental FPGA-centric Vu ...

We propose to design and build the Cyber Adversary Discovery Engine (CADE) for forensic cyber analysis. CADE combines expressive behavioral modeling technology with machine learning to automatically recognize adversary behaviors, goals and tactics, techniques and procedures (TTPs). CADE can further automatically recognize changes in adversary TTPs that occur in forensic data. A key technical capab ...

In this program, Physical Sciences Inc. (PSI) will team with Professor Ali Adibi’s group at the Georgia Institute of Technology to develop a photonic integrated circuit (PIC) spectrometer that can simultaneously achieve high-resolution over wide-bandwidths using a scalable and foundry-ready approach. While a PIC-based spectrometer is a key component for on-chip Raman, fluorescence, and absorptio ...

Our solution will provide an automated system driven by advanced analytics and machine learning techniques to capture network traffic (including potential malicious events), perform forensic analysis of the events to identify threat actor tactics, techniques, and procedures (TTPs), create a database of classified events and TTPs (threat models) from which connections can be made between events, ac ...

Quantum cascade laser optical output power is limited by laser facet catastrophic optical damage (COD). In edge-emitting semiconductor lasers COD is a thermal runaway process wherein the front facet of the laser heats under high power operation. This facet heating reduces the semiconductor bandgap which increases the optical absorption and also increases the electrical injection current in the fac ...

In this program, we will develop solutions to optimize QCL fabrication processes, such as facet passivation and high thermal conductivity coatings, that will mitigate the reliability issues for high power QCL applications. In phase I, we will first evaluate all concepts and efforts that have been largely investigated for GaAs based high power diode lasers and transfer the knowledge to InP based QC ...

The development of a catastrophic optical damage model for quantum cascade lasers describing instantaneous laser damage at high optical power levels is proposed. The model will be validated by comparison to experimental data. Based on obtained results, changes to laser design and laser fabrication resulting in an increased damage threshold will be implemented. The work will ultimately result into ...

Manufacturing of structural composites traditionally employs autoclaves to achieve high quality parts, including high fiber-volume-fractions and low porosity. A laminate comprised of stacked prepreg plies are cured under a vacuum in addition to ~7 bar of pressure to prevent formation of voids, particulalry in interlaminar (inter-sheet/ply) regions. However, manufacturing composites within an autoc ...