About

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.

Research topics

• Computer Science
• Political Science
• Artificial Intelligence
• Computer Security
• Sociology
• Management science
• Risk analysis (engineering)
• Business
• Engineering
• Engineering ethics
• Law

Selected publications

• When to Compute in Space

  2026-01-08

  articleSenior author

  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.

  PublisherDOI

• Adversarial Pursuits in Cislunar Space

  2026-01-08

  article

  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.

  PublisherDOI

• Out-of-Band Power Side-Channel Detection for Semiconductor Supply Chain Integrity at Scale

  arXiv (Cornell University) · 2026-01-03

  preprintOpen accessSenior author

  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.

  PublisherDOI

• Out-of-Band Power Side-Channel Detection for Semiconductor Supply Chain Integrity at Scale

  ArXiv.org · 2026-01-03

  articleOpen accessSenior author

  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.

  PublisherOA PDF

• Security of Emerging Satellite Mega-Constellations

  IEEE RESOURCE CENTERS · 2026-04-14

  otherOpen accessSenior author
  PublisherDOI

• Cyber Resilient Attitude Determination and Control for Space Vehicles

  2026-01-08

  articleSenior author

  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.

  PublisherDOI

• Situational Awareness for Proactive Rerouting: Enhancing Resilience in Submarine Communication Cables

  Open MIND · 2026-03-03

  articleOpen access
  OA PDFDOI

• When to compute in space

  ArXiv.org · 2025-12-18

  articleOpen accessSenior author

  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.

  PublisherOA PDF

• Testable Cyber Requirements for Space Flight Software

  2025-03-01

  articleSenior author

  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.

  PublisherDOI

• A Meta-Analysis of Radio Frequency Interactions in the Ionosphere and Near-Earth Space

  2025-01-03

  articleSenior author

  The ionosphere plays a pivotal role in radio frequency (RF) signal propagation, influencing critical infrastructure and services. This paper presents a comprehensive taxonomy of RF ionospheric and near-Earth space interactions, categorizing them into two primary domains: interactions with natural phenomena and artificial objects. By synthesizing findings from literature, we present a consolidation of key mechanisms, technological implications, and research gaps to serve as a compendium of RF interactions in the ionosphere and near-Earth space.

  PublisherDOI

Frequent coauthors

• Herbert Lin

  Stanford University

  23 shared

• Joshua Siegel

  20 shared

• Nicolò Boschetti

  Sibley Memorial Hospital

  15 shared

• Nathaniel G. Gordon

  Cornell University

  13 shared

• Eric Rosenbach

  11 shared

• Rajiv Thummala

  Cornell University

  10 shared

• Carsten Maple

  University of Warwick

  9 shared

• Arun Viswanathan

  Jet Propulsion Laboratory

  7 shared

Awards & honors

• Columbia University School of Professional Studies CUNY Fell…
• Columbia HBCU Fellowship Program