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Cornell University · American Language Program
Active 2015–2026
Gregory Falco is an Adjunct Professor at Columbia University, a Cyber Research Fellow at Harvard University, a Research Scholar at Stanford University, a Research Affiliate at MIT, and an incoming Assistant Professor at Johns Hopkins University. He has been at the forefront of smart city design, development, and deployment in industry and academia for over a decade. His research focuses on uncovering the security, safety, and trust risks of AI-enabled mission systems, and he invents and holds patents for security and resilience-enabling technology for terrestrial and space autonomous and control systems. Falco applies his research to sectors such as energy, space, public safety, transportation, and insurance. Prior to academia, he was an executive at Accenture, where he co-founded and led the Smart Cities division, developing strategies and technologies for utilities and city governments to improve environmental sustainability and operational efficiency. He holds a B.S. from Cornell University, an M.S. from Columbia University, and a Ph.D. from MIT.
2026-01-08
Spacecraft increasingly rely on heterogeneous computing resources spanning onboard flight computers, orbital data centers, ground station edge nodes, and terrestrial cloud infrastructure. Selecting where a workload should execute is a nontrivial multi objective problem driven by latency, reliability, power, communication constraints, cost, and regulatory feasibility. This paper introduces a quantitative optimization framework that formalizes compute‐location selection through empirically measurable metrics, normalized scoring, feasibility constraints, and a unified utility function designed to operate under incomplete information. We evaluate the model on two representative workloads demonstrating how the framework compares compute tiers and identifies preferred deployment locations. The approach provides a structured, extensible method for mission designers to reason about compute placement in emerging space architectures.
Herbert Lin
Stanford University
Joshua Siegel
Nicolò Boschetti
Sibley Memorial Hospital
Nathaniel G. Gordon
Cornell University
Eric Rosenbach
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Out-of-Band Power Side-Channel Detection for Semiconductor Supply Chain Integrity at Scale
arXiv (Cornell University) · 2026-01-03
Out-of-band screening of microcontrollers is a major gap in semiconductor supply chain security. High-assurance techniques such as X-ray and destructive reverse engineering are accurate but slow and expensive, hindering comprehensive detection for hardware Trojans or firmware tampering. Consequently, there has been increased interest in applying machine learning techniques to automate forensic examination, enabling rapid, large-scale inspection of components without manual oversight. We introduce a non-destructive screening method that uses power side-channel measurements and generative modeling to detect tampering in commodity microcontrollers without trusted hardware. As a proof-of-concept, differential power analysis (DPA) traces are collected from the ChipWhisperer and a generative adversarial network (GAN) is trained only on benign measurements to learn nominal power behavior. The trained discriminator then serves as a one-class anomaly detector. We report detection performance on multiple tampering scenarios and discuss how this technique can serve as an intermediate screening tier between basic functional tests and high-cost forensic analysis. The proposed method is evaluated in the context of semiconductor supply chain practice and policy to assess its suitability as an intermediate assurance mechanism.
Out-of-Band Power Side-Channel Detection for Semiconductor Supply Chain Integrity at Scale
ArXiv.org · 2026-01-03
Out-of-band screening of microcontrollers is a major gap in semiconductor supply chain security. High-assurance techniques such as X-ray and destructive reverse engineering are accurate but slow and expensive, hindering comprehensive detection for hardware Trojans or firmware tampering. Consequently, there has been increased interest in applying machine learning techniques to automate forensic examination, enabling rapid, large-scale inspection of components without manual oversight. We introduce a non-destructive screening method that uses power side-channel measurements and generative modeling to detect tampering in commodity microcontrollers without trusted hardware. As a proof-of-concept, differential power analysis (DPA) traces are collected from the ChipWhisperer and a generative adversarial network (GAN) is trained only on benign measurements to learn nominal power behavior. The trained discriminator then serves as a one-class anomaly detector. We report detection performance on multiple tampering scenarios and discuss how this technique can serve as an intermediate screening tier between basic functional tests and high-cost forensic analysis. The proposed method is evaluated in the context of semiconductor supply chain practice and policy to assess its suitability as an intermediate assurance mechanism.
Open MIND · 2026-03-03
Cyber Resilient Attitude Determination and Control for Space Vehicles
2026-01-08
Attitude determination and control systems (ADCS) represent critical single points of failure for spacecraft, yet their resilience against cyberattacks remains underexplored. This paper evaluates five attitude control architectures including PD, LQR+KF, neural surrogate, median ensemble, and hybrid, under post-compromise conditions using simulations on a genuine spaceflight computer. Through Monte Carlo simulations with sensor corruption, actuator tampering, timing delays, and model mismatch attacks, we demonstrate that learning-based controllers exhibit severe instability with crash rates of 70-100\%, while model-based controllers degrade predictably and maintain attitude authority. These results indicate that cyber-resilient ADCS for contested environments should prioritize model-based designs with stability guarantees, using learning-based methods only as auxiliary components with validated fallback strategies.
Adversarial Pursuits in Cislunar Space
2026-01-08
Cislunar space is becoming a critical domain for future lunar and interplanetary missions, yet its remoteness, sparse infrastructure, and unstable dynamics create single points of failure. Adversaries in cislunar orbits can exploit these vulnerabilities to pursue and jam co-located communication relays, potentially severing communications between lunar missions and the Earth. We study a pursuit-evasion scenario between two spacecraft in a cislunar orbit, where the evader must avoid a pursuer-jammer while remaining close to its nominal trajectory. We model the evader-pursuer interaction as a zero-sum adversarial differential game cast in the circular restricted three-body problem. This formulation incorporates critical aspects of cislunar orbital dynamics, including autonomous adjustment of the reference orbit phasing to enable aggressive evading maneuvers, and shaping of the evader’s cost with the orbit’s stable and unstable manifolds. We solve the resulting nonlinear game locally using a continuous-time differential dynamic programming variant, which iteratively applies linear-quadratic approximations to the Hamilton-Jacobi-Isaacs equation. We simulate the evader’s behavior against both a worst-case and a linear-quadratic pursuer. Our results pave the way for securing future missions in cislunar space against emerging cyber threats.
Security of Emerging Satellite Mega-Constellations
IEEE RESOURCE CENTERS · 2026-04-14
Testable Cyber Requirements for Space Flight Software
2025-03-01
As space missions grow in complexity, the cybersecurity threat landscape expands, necessitating a shift toward secure-by-design flight software (FSW). Traditional development prioritizes functionality over security, leaving systems vulnerable to attack. This paper introduces a novel methodology for developing cyber-resilient FSW with a secure-by-component architecture. By incorporating key resilience principles—segmentation, adaptive response, redundancy, and substantiated integrity—our approach addresses critical security needs early in development, minimizing attack surfaces without sacrificing performance. Leveraging NIST systems security guidelines and tailored cyber resilience techniques, we apply this methodology to a notional spacecraft's Command and Data Handling (C&DH) subsystem. Through attack surface analysis and threat modeling, we derive specific cybersecurity requirements to enhance resilience. Key mechanisms, such as real-time monitoring, cryptographic enforcement, memory-safe programming, and zero-trust communication, are embedded to mitigate vulnerabilities from external threats and internal faults. This work advances space cybersecurity by offering a scalable, secure-by-design approach to FSW. Future efforts will extend this methodology to formal verification and autonomous systems, ensuring space operations remain secure against evolving adversarial tactics.
2025-11-12
Low Earth Orbit (LEO) mega-constellations have catalyzed interest in on-orbit computing, but an exclusive focus on LEO risks architectural bottlenecks in custody duration and end-to-end latency. We introduce a multi-orbit, space-based fog architecture that couples Medium Earth Orbit (MEO) and LEO constellations to share sensing, communication, and on-orbit processing. Unlike relay-centric designs, the proposed cumulonimbus-like fog computing (CLFC) framework assigns MEO nodes active roles in segmentation, intermediate inference, and fusion while leveraging dense LEO meshes for parallel CNN execution. Using access geometry and image-processing models grounded in prior onboard benchmarks, we show (i) an order-of-magnitude increase in chain-of-custody duration relative to an LEO-only baseline and (ii) up to a 94% reduction in processing latency via inter-orbital parallelism. A preliminary trade study further indicates that CLFC can reproduce Starlink-like network presence with only <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{1 3}-\mathbf{7 3} \boldsymbol{\%}$</tex> of the LEO satellite count, highlighting efficiency gains for sparsely populated constellations. These results position multi-orbit fog computing as a practical path to real-time hypersonic detection and space domain awareness without dependence on terrestrial cloud resources.
Space Cybersecurity Incident Response Framework: A Viasat Case Study
2025-03-01 · 2 citations
The restoration of space systems following failures has historically been precipitated by natural phenomena such as geomagnetic storms or unintentional software malfunctions and hardware issues. However, the advent of intentional cyber-attacks targeting space systems heralds a new era of incident response. This paper presents a first-hand account of the incident response to the February 2022 cyberattack on Viasat's KA-SAT network, which coincided with the Russian invasion of Ukraine. Lessons learned are highlighted and integrated into a proposed incident response framework for space system service providers.
Rajiv Thummala
Cornell University
Carsten Maple
University of Warwick
Arun Viswanathan
Jet Propulsion Laboratory