arXiv subjects

Gruia-Catalin Roman

Publications and source records attributed to Gruia-Catalin Roman.

4 recordsLinked to original sources

arXiv2026

Trust Without Boundaries: An Architectural Analysis of Satellite Flight Software

As spacecraft become more software-driven and interconnected, onboard flight software is an increasingly important security boundary. Popular flight software architectures often treat onboard components as trusted peers, simplifying integration while limiting internal isolation and access control. We analyze NASA's Core Flight Software (cFS) to examine how authority, identity, communication, observability, and persistence are distributed across onboard components. Using NASA's flight-representative NOS3 simulator, we validate these weaknesses through five experiments implemented with a malicious onboard component that abuses legitimate architectural privileges. We then compare cFS with other modular flight software frameworks to identify recurring trust assumptions and architectural weaknesses. Our results show that a single compromised component can exploit broadly shared authority in ways that are difficult to distinguish from legitimate behavior. We conclude with architectural implications and discuss mechanisms for strengthening internal trust boundaries in future flight software systems.

cs.CR↗

arXiv2026

Silent Subversion: Sensor Spoofing Attacks via Supply Chain Implants in Satellite Systems

Spoofing attacks are among the most destructive cyber threats to terrestrial systems, and they become even more dangerous in space, where satellites cannot be easily serviced, and operators depend on accurate telemetry to ensure mission success. When telemetry is compromised, entire spaceborne missions are placed at risk. Prior work on spoofing has largely focused on attacks from Earth, such as injecting falsified uplinks or overpowering downlinks with stronger radios. In contrast, onboard spoofing originating from within the satellite itself remains an underexplored and underanalyzed threat. This vector is particularly concerning given that modern satellites, especially small satellites, rely on modular architectures and globalized supply chains that reduce cost and accelerate development but also introduce hidden risks. This paper presents an end-to-end demonstration of an internal satellite spoofing attack delivered through a compromised vendor-supplied component implemented in NASA's NOS3 simulation environment. Our rogue Core Flight Software application passed integration and generated packets in the correct format and cadence that the COSMOS ground station accepted as legitimate. By undermining both onboard estimators and ground operator views, the attack directly threatens mission integrity and availability, as corrupted telemetry can bias navigation, conceal subsystem failures, and mislead operators into executing harmful maneuvers. These results expose component-level telemetry spoofing as an overlooked supply-chain vector distinct from jamming or external signal injection. We conclude by discussing practical countermeasures-including authenticated telemetry, component attestation, provenance tracking, and lightweight runtime monitoring-and highlight the trade-offs required to secure resource-constrained small satellites.

cs.CR↗

arXiv2025

SpyChain: Multi-Vector Supply Chain Attacks on Small Satellite Systems

Small satellites are integral to scientific, commercial, and defense missions, but reliance on commercial off-the-shelf (COTS) hardware broadens their attack surface. Although supply chain threats are well studied in other cyber-physical domains, their feasibility and stealth in space systems remain largely unexplored. Prior work has focused on flight software, which benefits from strict security practices and oversight. In contrast, auxiliary COTS components often lack robust assurance yet enjoy comparable access to critical on-board resources, including telemetry, system calls, and the software bus. Despite this privileged access, the insider threat within COTS hardware supply chains has received little attention. In this work, we present SpyChain, the first end-to-end design and implementation of independent and colluding hardware supply chain threats targeting small satellites. Using NASA's satellite simulation (NOS3), we demonstrate that SpyChain can evade testing, exfiltrate telemetry, disrupt operations, and launch Denial of Service (DoS) attacks through covert channels that bypass ground monitoring. Our study traces an escalation from a simple solo component to dynamic, coordinating malware, introducing a taxonomy of stealth across five scenarios. We showcase how implicit trust in auxiliary components enables covert persistence and reveal novel attack vectors, highlighting a new multi-component execution technique that is now incorporated into the SPARTA matrix. Our findings are reinforced by acknowledgment and affirmation from NASA's NOS3 team. Finally, we implement lightweight onboard defenses, including runtime monitoring, to mitigate threats like SpyChain.

cs.CR↗

arXiv2020

rIoT: Enabling Seamless Context-Aware Automation in the Internet of Things

Advances in mobile computing capabilities and an increasing number of Internet of Things (IoT) devices have enriched the possibilities of the IoT but have also increased the cognitive load required of IoT users. Existing context-aware systems provide various levels of automation in the IoT. Many of these systems adaptively take decisions on how to provide services based on assumptions made a priori. The approaches are difficult to personalize to an individual's dynamic environment, and thus today's smart IoT spaces often demand complex and specialized interactions with the user in order to provide tailored services. We propose rIoT, a framework for seamless and personalized automation of human-device interaction in the IoT. rIoT leverages existing technologies to operate across heterogeneous devices and networks to provide a one-stop solution for device interaction in the IoT. We show how rIoT exploits similarities between contexts and employs a decision-tree like method to adaptively capture a user's preferences from a small number of interactions with the IoT space. We measure the performance of rIoT on two real-world data sets and a real mobile device in terms of accuracy, learning speed, and latency in comparison to two state-of-the-art machine learning algorithms.

cs.CY↗