arXiv subjects

Simon Birnbach

Publications and source records attributed to Simon Birnbach.

12 recordsLinked to original sources

arXiv2025

VET Your Agent: Towards Host-Independent Autonomy via Verifiable Execution Traces

Recent advances in large language models (LLMs) have enabled a new generation of autonomous agents that operate over sustained periods and manage sensitive resources on behalf of users. Trusted for their ability to act without direct oversight, such agents are increasingly considered in high-stakes domains including financial management, dispute resolution, and governance. Yet in practice, agents execute on infrastructure controlled by a host, who can tamper with models, inputs, or outputs, undermining any meaningful notion of autonomy. We address this gap by introducing VET (Verifiable Execution Traces), a formal framework that achieves host-independent authentication of agent outputs and takes a step toward host-independent autonomy. Central to VET is the Agent Identity Document (AID), which specifies an agent's configuration together with the proof systems required for verification. VET is compositional: it supports multiple proof mechanisms, including trusted hardware, succinct cryptographic proofs, and notarized TLS transcripts (Web Proofs). We implement VET for an API-based LLM agent and evaluate our instantiation on realistic workloads. We find that for today's black-box, secret-bearing API calls, Web Proofs appear to be the most practical choice, with overhead typically under 3$\times$ compared to direct API calls, while for public API calls, a lower-overhead TEE Proxy is often sufficient. As a case study, we deploy a verifiable trading agent that produces proofs for each decision and composes Web Proofs with a TEE Proxy. Our results demonstrate that practical, host-agnostic authentication is already possible with current technology, laying the foundation for future systems that achieve full host-independent autonomy.

cs.CR↗

arXiv2025

DSNS: The Deep Space Network Simulator

Simulation tools are commonly used in the development and testing of new protocols or new networks. However, as satellite networks start to grow to encompass thousands of nodes, and as companies and space agencies begin to realize the interplanetary internet, existing satellite and network simulation tools have become impractical for use in this context. We therefore present the Deep Space Network Simulator (DSNS): a new network simulator with a focus on large-scale satellite networks. We demonstrate its improved capabilities compared to existing offerings, showcase its flexibility and extensibility through an implementation of existing protocols and the DTN simulation reference scenarios recommended by CCSDS, and evaluate its scalability, showing that it exceeds existing tools while providing better fidelity. DSNS provides concrete usefulness to both standards bodies and satellite operators, enabling fast iteration on protocol development and testing of parameters under highly realistic conditions. By removing roadblocks to research and innovation, we can accelerate the development of upcoming satellite networks and ensure that their communication is both fast and secure.

cs.NI↗

arXiv2025

SATversary: Adversarial Attacks and Defenses for Satellite Fingerprinting

Due to the increasing threat of attacks on satellite systems, novel countermeasures have been developed to provide additional security. Among these, there has been a particular interest in transmitter fingerprinting, which authenticates transmitters by looking at characteristics expressed in the physical layer signal. These systems rely heavily upon statistical methods and machine learning, and are therefore vulnerable to a range of attacks. The severity of this threat in a fingerprinting context is currently not well understood. In this paper we evaluate a range of attacks against satellite fingerprinting, building on previous works by looking at attacks optimized to target the fingerprinting system for maximal impact. We design optimized jamming, dataset poisoning, and spoofing attacks, evaluating them in the real world against the SatIQ fingerprinting system designed to authenticate Iridium transmitters, and using a wireless channel emulator to achieve realistic channel conditions. We show that an optimized jamming signal can cause a 50% error rate with attacker-to-victim ratios as low as -30dB (far less power than traditional jamming techniques), and demonstrate successful spoofing attacks, with an attacker successfully removing their own transmitter's fingerprint from messages. We also present a viable dataset poisoning attack, enabling persistent message spoofing by altering stored data to include the fingerprint of the attacker's transmitter. Finally, we show that a model trained to optimize spoofing attacks can also be used to detect spoofing and replay attacks, even when it has never seen the attacker's transmitter before. This technique works even when the training dataset includes only a single transmitter, enabling fingerprinting to be used to protect small constellations and even individual satellites, providing additional protection where it is needed the most.

cs.CR↗

arXiv2024

KeySpace: Enhancing Public Key Infrastructure for Interplanetary Networks

As the use of satellites continues to grow, new networking paradigms are emerging to support the scale and long distance communication inherent to these networks. In particular, interplanetary communication relays connect distant network segments together, but result in a sparsely connected network with long-distance links that are frequently interrupted. In this new context, traditional Public Key Infrastructure (PKI) becomes difficult to implement, due to the impossibility of low-latency queries to a central authority. This paper addresses the challenge of implementing PKI in these complex networks, identifying the essential goals and requirements. Using these requirements, we develop the KeySpace framework, comprising a set of standardized experiments and metrics for comparing PKI systems across various network topologies, evaluating their performance and security. This enables the testing of different protocols and configurations in a standard, repeatable manner, so that improvements can be more fairly tested and clearly demonstrated. We use KeySpace to test two standard PKI protocols in use in terrestrial networks (OCSP and CRLs), demonstrating for the first time that both can be effectively utilized even in interplanetary networks with high latency and frequent interruptions, provided authority is properly distributed throughout the network. Finally, we propose and evaluate a number of novel techniques extending standard OCSP to improve the overhead of connection establishment, reduce link congestion, and limit the reach of an attacker with a compromised key. Using KeySpace we validate these claims, demonstrating their improved performance over the state of the art.

cs.CR↗

arXiv2024

Sticky Fingers: Resilience of Satellite Fingerprinting against Jamming Attacks

In the wake of increasing numbers of attacks on radio communication systems, a range of techniques are being deployed to increase the security of these systems. One such technique is radio fingerprinting, in which the transmitter can be identified and authenticated by observing small hardware differences expressed in the signal. Fingerprinting has been explored in particular in the defense of satellite systems, many of which are insecure and cannot be retrofitted with cryptographic security. In this paper, we evaluate the effectiveness of radio fingerprinting techniques under interference and jamming attacks, usually intended to deny service. By taking a pre-trained fingerprinting model and gathering a new dataset in which different levels of Gaussian noise and tone jamming have been added to the legitimate signal, we assess the attacker power required in order to disrupt the transmitter fingerprint such that it can no longer be recognized. We compare this to Gaussian jamming on the data portion of the signal, obtaining the remarkable result that transmitter fingerprints are still recognizable even in the presence of moderate levels of noise. Through deeper analysis of the results, we conclude that it takes a similar amount of jamming power in order to disrupt the fingerprint as it does to jam the message contents itself, so it is safe to include a fingerprinting system to authenticate satellite communication without opening up the system to easier denial-of-service attacks.

cs.CR↗

arXiv2023

Watch This Space: Securing Satellite Communication through Resilient Transmitter Fingerprinting

Due to an increase in the availability of cheap off-the-shelf radio hardware, spoofing and replay attacks on satellite ground systems have become more accessible than ever. This is particularly a problem for legacy systems, many of which do not offer cryptographic security and cannot be patched to support novel security measures. In this paper we explore radio transmitter fingerprinting in satellite systems. We introduce the SatIQ system, proposing novel techniques for authenticating transmissions using characteristics of transmitter hardware expressed as impairments on the downlinked signal. We look in particular at high sample rate fingerprinting, making fingerprints difficult to forge without similarly high sample rate transmitting hardware, thus raising the budget for attacks. We also examine the difficulty of this approach with high levels of atmospheric noise and multipath scattering, and analyze potential solutions to this problem. We focus on the Iridium satellite constellation, for which we collected 1705202 messages at a sample rate of 25 MS/s. We use this data to train a fingerprinting model consisting of an autoencoder combined with a Siamese neural network, enabling the model to learn an efficient encoding of message headers that preserves identifying information. We demonstrate the system's robustness under attack by replaying messages using a Software-Defined Radio, achieving an Equal Error Rate of 0.120, and ROC AUC of 0.946. Finally, we analyze its stability over time by introducing a time gap between training and testing data, and its extensibility by introducing new transmitters which have not been seen before. We conclude that our techniques are useful for building systems that are stable over time, can be used immediately with new transmitters without retraining, and provide robustness against spoofing and replay by raising the required budget for attacks.

cs.CR↗

arXiv2023

POSTER: spaceQUIC: Securing Communication in Computationally Constrained Spacecraft

Recent years have seen a rapid increase in the number of CubeSats and other small satellites in orbit - these have highly constrained computational and communication resources, but still require robust secure communication to operate effectively. The QUIC transport layer protocol is designed to provide efficient communication with cryptography guarantees built-in, with a particular focus on networks with high latency and packet loss. In this work we provide spaceQUIC, a proof of concept implementation of QUIC for NASA's "core Flight System" satellite operating system, and assess its performance.

cs.CR↗

arXiv2023

RADAR: A TTP-based Extensible, Explainable, and Effective System for Network Traffic Analysis and Malware Detection

Network analysis and machine learning techniques have been widely applied for building malware detection systems. Though these systems attain impressive results, they often are $(i)$ not extensible, being monolithic, well tuned for the specific task they have been designed for but very difficult to adapt and/or extend to other settings, and $(ii)$ not interpretable, being black boxes whose inner complexity makes it impossible to link the result of detection with its root cause, making further analysis of threats a challenge. In this paper we present RADAR, an extensible and explainable system that exploits the popular TTP (Tactics, Techniques, and Procedures) ontology of adversary behaviour described in the industry-standard MITRE ATT\&CK framework in order to unequivocally identify and classify malicious behaviour using network traffic. We evaluate RADAR on a very large dataset comprising of 2,286,907 malicious and benign samples, representing a total of 84,792,452 network flows. The experimental analysis confirms that the proposed methodology can be effectively exploited: RADAR's ability to detect malware is comparable to other state-of-the-art non-interpretable systems' capabilities. To the best of our knowledge, RADAR is the first TTP-based system for malware detection that uses machine learning while being extensible and explainable.

cs.CR↗

arXiv2023

Dishing Out DoS: How to Disable and Secure the Starlink User Terminal

Satellite user terminals are a promising target for adversaries seeking to target satellite communication networks. Despite this, many protections commonly found in terrestrial routers are not present in some user terminals. As a case study we audit the attack surface presented by the Starlink router's admin interface, using fuzzing to uncover a denial of service attack on the Starlink user terminal. We explore the attack's impact, particularly in the cases of drive-by attackers, and attackers that are able to maintain a continuous presence on the network. Finally, we discuss wider implications, looking at lessons learned in terrestrial router security, and how to properly implement them in this new context.

cs.CR↗

arXiv2022

RingAuth: Wearable Authentication using a Smart Ring

In this paper, we show that by using inertial sensor data generated by a smart ring, worn on the finger, the user can be authenticated when making mobile payments or when knocking on a door (for access control). The proposed system can be deployed purely in software and does not require updates to existing payment terminals or infrastructure. We also demonstrate that smart ring data can authenticate smartwatch gestures, and vice versa, allowing either device to act as an implicit second factor for the other. To validate the system, we conduct a user study (n=21) to collect inertial sensor data from users as they perform gestures, and we evaluate the system against an active impersonation attacker. Based on this data, we develop payment and access control authentication models for which we achieve EERs of 0.04 and 0.02, respectively.

cs.CR↗

arXiv2022

BeeHIVE: Behavioral Biometric System based on Object Interactions in Smart Environments

The lack of standard input interfaces in the Internet of Things (IoT) ecosystems presents a challenge in securing such infrastructures. To tackle this challenge, we introduce a novel behavioral biometric system based on naturally occurring interactions with objects in smart environments. This biometric leverages existing sensors to authenticate users without requiring any hardware modifications of existing smart home devices. The system is designed to reduce the need for phone-based authentication mechanisms, on which smart home systems currently rely. It requires the user to approve transactions on their phone only when the user cannot be authenticated with high confidence through their interactions with the smart environment. We conduct a real-world experiment that involves 13 participants in a company environment, using this experiment to also study mimicry attacks on our proposed system. We show that this system can provide seamless and unobtrusive authentication while still staying highly resistant to zero-effort, video, and in-person observation-based mimicry attacks. Even when at most 1% of the strongest type of mimicry attacks are successful, our system does not require the user to take out their phone to approve legitimate transactions in more than 80% of cases for a single interaction. This increases to 92% of transactions when interactions with more objects are considered.

cs.CR↗

arXiv2021

They See Me Rollin': Inherent Vulnerability of the Rolling Shutter in CMOS Image Sensors

In this paper, we describe how the electronic rolling shutter in CMOS image sensors can be exploited using a bright, modulated light source (e.g., an inexpensive, off-the-shelf laser), to inject fine-grained image disruptions. We demonstrate the attack on seven different CMOS cameras, ranging from cheap IoT to semi-professional surveillance cameras, to highlight the wide applicability of the rolling shutter attack. We model the fundamental factors affecting a rolling shutter attack in an uncontrolled setting. We then perform an exhaustive evaluation of the attack's effect on the task of object detection, investigating the effect of attack parameters. We validate our model against empirical data collected on two separate cameras, showing that by simply using information from the camera's datasheet the adversary can accurately predict the injected distortion size and optimize their attack accordingly. We find that an adversary can hide up to 75% of objects perceived by state-of-the-art detectors by selecting appropriate attack parameters. We also investigate the stealthiness of the attack in comparison to a naïve camera blinding attack, showing that common image distortion metrics can not detect the attack presence. Therefore, we present a new, accurate and lightweight enhancement to the backbone network of an object detector to recognize rolling shutter attacks. Overall, our results indicate that rolling shutter attacks can substantially reduce the performance and reliability of vision-based intelligent systems.

cs.CV↗