arXiv subjects

Gregory Falco

Publications and source records attributed to Gregory Falco.

15 recordsLinked to original sources

arXiv2026

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

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.

cs.CR↗

arXiv2025

When to compute in space

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.

cs.CE↗

arXiv2025

Adversarial Pursuits in Cislunar Space

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.

eess.SY↗

arXiv2025

Securing Heterogeneous Network (HetNet) Communications for Wildfire Management: Mitigating the Effects of Adversarial and Environmental Threats

In the face of adverse environmental conditions and cyber threats, robust communication systems for critical applications such as wildfire management and detection demand secure and resilient architectures. This paper presents a novel framework that considers both adversarial factors, building resilience into a heterogeneous network (HetNet) integrating Low Earth Orbit (LEO) satellite constellation with High-Altitude Platform Ground Stations (HAPGS) and Low-Altitude Platforms (LAPS), tailored to support wildfire management operations. Building upon our previous work on secure-by-component approach for link segment security, we extend protection to the communication layer by securing both Radio Frequency (RF)/Free Space Optics (FSO) management and different links. Through a case study, we quantify how environmental stressors impact secrecy capacity and expose the system to passive adversaries. Key findings demonstrate that atmospheric attenuation and beam misalignment can notably degrade secrecy capacity across both short- and long-range communication links, while high-altitude eavesdroppers face less signal degradation, increasing their interception capability. Moreover, increasing transmit power to counter environmental losses can inadvertently improve eavesdropper reception, thereby reducing overall link confidentiality. Our work not only highlights the importance of protecting networks from these dual threats but also aligns with the IEEE P3536 Standard for Space System Cybersecurity Design, ensuring resilience and the prevention of mission failures.

cs.CR↗

arXiv2025

I Can Hear You Coming: RF Sensing for Uncooperative Satellite Evasion

This work presents a novel method for leveraging intercepted Radio Frequency (RF) signals to inform a constrained Reinforcement Learning (RL) policy for robust control of a satellite operating in contested environments. Uncooperative satellite engagements with nation-state actors prompts the need for enhanced maneuverability and agility on-orbit. However, robust, autonomous and rapid adversary avoidance capabilities for the space environment is seldom studied. Further, the capability constrained nature of many space vehicles does not afford robust space situational awareness capabilities that can be used for well informed maneuvering. We present a "Cat & Mouse" system for training optimal adversary avoidance algorithms using RL. We propose the novel approach of utilizing intercepted radio frequency communication and dynamic spacecraft state as multi-modal input that could inform paths for a mouse to outmaneuver the cat satellite. Given the current ubiquitous use of RF communications, our proposed system can be applicable to a diverse array of satellites. In addition to providing a comprehensive framework for training and implementing a constrained RL policy capable of providing control for robust adversary avoidance, we also explore several optimization based methods for adversarial avoidance. These methods were then tested on real-world data obtained from the Space Surveillance Network (SSN) to analyze the benefits and limitations of different avoidance methods.

cs.RO↗

arXiv2024

Adaptive Detection of On-Orbit Jamming for Securing GEO Satellite Links

This paper introduces a scenario where a maneuverable satellite in geostationary orbit (GEO) conducts on-orbit attacks, targeting communication between a GEO satellite and a ground station, with the ability to switch between stationary and time-variant jamming modes. We propose a machine learning-based detection approach, employing the random forest algorithm with principal component analysis (PCA) to enhance detection accuracy in the stationary model. At the same time, an adaptive threshold-based technique is implemented for the time-variant model to detect dynamic jamming events effectively. Our methodology emphasizes the need for the use of orbital dynamics in integrating physical constraints from satellite dynamics to improve model robustness and detection accuracy. Simulation results highlight the effectiveness of PCA in enhancing the performance of the stationary model, while the adaptive thresholding method achieves high accuracy in detecting jamming in the time-variant scenario. This approach provides a robust solution for mitigating the evolving threats to satellite communication in GEO environments.

eess.SP↗

arXiv2024

Securing Satellite Link Segment: A Secure-by-Component Design

The rapid evolution of communication technologies, compounded by recent geopolitical events such as the Viasat cyberattack in February 2022, has highlighted the urgent need for fast and reliable satellite missions for military and civil security operations. Consequently, this paper examines two Earth observation (EO) missions: one utilizing a single low Earth orbit (LEO) satellite and another through a network of LEO satellites, employing a secure-by-component design strategy. This approach begins by defining the scope of technical security engineering, decomposing the system into components and data flows, and enumerating attack surfaces. Then it proceeds by identifying threats to low-level components, applying secure-by-design principles, redesigning components into secure blocks in alignment with the Space Attack Research & Tactic Analysis (SPARTA) framework, and crafting shall statements to refactor the system design, with a particular focus on improving the security of the link segment.

cs.CR↗

arXiv2024

Satellite Chasers: Divergent Adversarial Reinforcement Learning to Engage Intelligent Adversaries on Orbit

As space becomes increasingly crowded and contested, robust autonomous capabilities for multi-agent environments are gaining critical importance. Current autonomous systems in space primarily rely on optimization-based path planning or long-range orbital maneuvers, which have not yet proven effective in adversarial scenarios where one satellite is actively pursuing another. We introduce Divergent Adversarial Reinforcement Learning (DARL), a two-stage Multi-Agent Reinforcement Learning (MARL) approach designed to train autonomous evasion strategies for satellites engaged with multiple adversarial spacecraft. Our method enhances exploration during training by promoting diverse adversarial strategies, leading to more robust and adaptable evader models. We validate DARL through a cat-and-mouse satellite scenario, modeled as a partially observable multi-agent capture the flag game where two adversarial ``cat" spacecraft pursue a single ``mouse" evader. DARL's performance is compared against several benchmarks, including an optimization-based satellite path planner, demonstrating its ability to produce highly robust models for adversarial multi-agent space environments.

cs.RO↗

arXiv2024

On the Role of Communications for Space Domain Awareness

Space Domain Awareness (SDA) has become increasingly vital with the rapid growth of commercial space activities and the expansion of New Space. This paper stresses the necessity of transitioning from centralized to distributed SDA architectures. The current architecture predominantly relies on individual downhaul, which we propose to transition to on-orbit distribution. Our results demonstrate that the individual downhaul architecture does not scale efficiently with the increasing number of nodes, while on-orbit distribution offers significant improvements. By comparing the centralized architecture with the proposed distributed architecture, we highlight the advantages of enhanced coverage and resilience. Our findings show that on-orbit distribution greatly outperforms individual downhaul in terms of latency and scalability. Specifically, the latency results for on-orbit distribution are substantially lower and more consistent, even as the number of satellites increases. In addition, we address the inherent challenges associated with on-orbit distribution architecture, particularly cybersecurity concerns. We focus on link security to ensure the availability and integrity of data transmission in these advanced SDA systems. Future expectations include further refinement of on-orbit distribution strategies and the development of robust cybersecurity measures to support the scalability and resilience of SDA systems.

cs.ET↗

arXiv2024

Adversarial Machine Learning Threats to Spacecraft

Spacecraft are among the earliest autonomous systems. Their ability to function without a human in the loop have afforded some of humanity's grandest achievements. As reliance on autonomy grows, space vehicles will become increasingly vulnerable to attacks designed to disrupt autonomous processes-especially probabilistic ones based on machine learning. This paper aims to elucidate and demonstrate the threats that adversarial machine learning (AML) capabilities pose to spacecraft. First, an AML threat taxonomy for spacecraft is introduced. Next, we demonstrate the execution of AML attacks against spacecraft through experimental simulations using NASA's Core Flight System (cFS) and NASA's On-board Artificial Intelligence Research (OnAIR) Platform. Our findings highlight the imperative for incorporating AML-focused security measures in spacecraft that engage autonomy.

cs.LG↗

arXiv2024

Hacktivism Goes Orbital: Investigating NB65's Breach of ROSCOSMOS

In March of 2022, Network battalion 65 (NB65), a hacktivist affiliate of Anonymous, publicly asserted its successful breach of ROSCOSMOS's satellite imaging capabilities in response to Russia's invasion of Ukraine. NB65 disseminated a series of primary sources as substantiation, proclaiming the incapacitation of ROSCOSMOS's space-based vehicle monitoring system and doxing of related proprietary documentation. Despite the profound implications of hacktivist incursions into the space sector, the event has garnered limited attention due to the obscurity of technical attack vectors and ROCOSMOS's denial of NB65's allegations. Through analysis of NB65's released primary sources of evidence, this paper uncovers the probable vulnerabilities and exploits that enabled the alleged breach into ROSCOSMOS's ground and space segment. Additionally, we highlight lessons learned and the consequences this event has for the global aerospace community.

cs.CR↗

arXiv2021

Cyberphysical Sequencing for Distributed Asset Management with Broad Traceability

Cyber-Physical systems (CPS) have complex lifecycles involving multiple stakeholders, and the transparency of both hardware and software components' supply chain is opaque at best. This raises concerns for stakeholders who may not trust that what they receive is what was requested. There is an opportunity to build a cyberphysical titling process offering universal traceability and the ability to differentiate systems based on provenance. Today, RFID tags and barcodes address some of these needs, though they are easily manipulated due to non-linkage with an object or system's intrinsic characteristics. We propose cyberphysical sequencing as a low-cost, light-weight and pervasive means of adding track-and-trace capabilities to any asset that ties a system's physical identity to a unique and invariant digital identifier. CPS sequencing offers benefits similar Digital Twins' for identifying and managing the provenance and identity of an asset throughout its life with far fewer computational and other resources.

cs.CR↗

arXiv2021

Cyber Crossroads: A Global Research Collaborative on Cyber Risk Governance

Spending on cybersecurity products and services is expected to top 123 billion U.S. dollars for 2020, more than double the 55 billion U.S. dollars spent in 2011.1 In that same period, cyber breaches quadrupled. Organizations globally face increasing liabilities, while boards of directors grapple with a seemingly Sisyphean challenge. Cyber Crossroads was born out of these alarming trends and a realization that the world cannot go on funneling finite resources into an indefinite, intractable problem. Cyber Crossroads brings together expertise from across the world, spanning aspects of the cyber problem (including technology, legal, risk, and economic) with the goal of creating a Cyber Standard of Care built through a global, not-for-profit research collaborative with no commercial interests. A Cyber Standard of Care should be applicable across industries and regardless of the organization size. It should be practical and implementable, with no requirement to purchase any product/service. Cyber Standard of Care should be woven into the existing governance fabric of the organization and it should not be yet another technical checklist, but a process/governance framework that can stand over time. To achieve this, we engaged with cyber risk experts and practitioners with a variety of relevant expertise, secured the advice/guidance of regulators and legal experts across jurisdictions, and interviewed leaders from 56 organizations globally to understand their challenges and identify best practices.

cs.CY↗

arXiv2020

A Distributed `Black Box' Audit Trail Design Specification for Connected and Automated Vehicle Data and Software Assurance

Automotive software is increasingly complex and critical to safe vehicle operation, and related embedded systems must remain up-to-date to ensure long-term system performance. Update mechanisms and data modification tools introduce opportunities for malicious actors to compromise these cyber-physical systems, and for trusted actors to mistakenly install incompatible software versions. A distributed and stratified "black box" audit trail for automotive software and data provenance is proposed to assure users, service providers, and original equipment manufacturers (OEMs) of vehicular software integrity and reliability. The proposed black box architecture is both layered and diffuse, employing distributed hash tables (DHT), a parity system and a public blockchain to provide high resilience, assurance, scalability, and efficiency for automotive and other high-assurance systems.

cs.CR↗

arXiv2020

Death by AI: Where Assured Autonomy in Smart Cities Meets the End-to-End Argument

A smart city involves critical infrastructure systems that have been digitally enabled. Increasingly, many smart city cyber-physical systems are becoming automated. The extent of automation ranges from basic logic gates to sophisticated, artificial intelligence (AI) that enables fully autonomous systems. Because of modern society's reliance on autonomous systems in smart cities, it is crucial for them to operate in a safe manner; otherwise, it is feasible for these systems to cause considerable physical harm or even death. Because smart cities could involve thousands of autonomous systems operating in concert in densely populated areas, safety assurances are required. Challenges abound to consistently manage the safety of such autonomous systems due to their disparate developers, manufacturers, operators and users. A novel network and a sample of associated network functions for autonomous systems is proposed that aims to provide a baseline of safety for autonomous systems. This is accomplished by establishing a custom-designed network for autonomous systems that is separate from the Internet, and can handle certain functions that enable safety through active networking. Such a network design sits at the margins of the end-to-end principle, which is warranted considering the safety of autonomous systems is at stake as is argued in this paper. Without a scalable safety strategy for autonomous systems as proposed, assured autonomy in smart cities will remain elusive.

cs.CY↗