arXiv subjects

Quintus Kilbourn

Publications and source records attributed to Quintus Kilbourn.

4 recordsLinked to original sources

arXiv2026

Threat Vectors and the State of the Art in Defense Methods for Security in Neurotechnology

Brain-computer interfaces (BCIs) are a class of diverse hardware modalities, associated software, and connected devices which are widely used in a variety of fields, including neurosurgery, biomedical data analysis, and neuroimaging. Recent years have seen rapid advancements in BCI technology, and neurotechnology more broadly, with the first devices now passing clinical trials, early examples of consumer hardware entering the market, and many variants of consumer and medical hardware with increasingly extensive capabilities being developed rapidly. However, research and development in security for BCIs--known as neurosecurity--lags significantly behind the capabilities of BCIs themselves. In an effort to address as many vulnerabilities as feasible immediately, in this paper we review the current state of the art in neurosecurity, thoroughly survey the breadth and complexity of both firmly established and highly probable security threats to BCI systems, and provide recommendations of existing methods from cybersecurity, hardware security, and machine learning which can immediately be applied to address some of these gaps in neurosecurity.

cs.CR↗

arXiv2025

Proof of Cloud: Data Center Execution Assurance for Confidential VMs

Confidential Virtual Machines (CVMs) protect data in use by running workloads within hardware-enforced Trusted Execution Environments (TEEs). However, existing CVM attestation mechanisms only certify what code is running, not where it is running. Commercial TEEs mitigate passive physical attacks through memory encryption but explicitly exclude active hardware tampering (memory interposers, physical side channels, ...). Yet current attestations provide no cryptographic evidence that a CVM executes on hardware residing within a trusted data center where such attacks would not take place. This gap enables proxy attacks in which valid attestations are combined across machines to falsely attest trusted execution. To bridge this gap, we introduce Data Center Execution Assurance (DCEA), a design that generates a cryptographic Proof of Cloud by binding CVM attestation to platform-level Trusted Platform Module (TPM) evidence. DCEA combines two independent roots of trust. First, the TEE manufacturer, and second, the infrastructure provider, by cross-linking runtime TEE measurements with the vTPM-measured boot CVM state. This binding ensures that CVM execution, vTPM quotes, and platform provenance all originate from the same physical chassis. We formalize the environment's provenance and show that DCEA prevents advanced relay attacks, including a novel mix-and-match proxy attack. Using the AGATE framework in the Universal Composability model, we prove that DCEA emulates an ideal location-aware TEE even under a malicious host software stack. We implement DCEA on Google Cloud bare-metal Intel TDX instances using Intel TXT and evaluate its performance, demonstrating practical overheads and deployability. DCEA refines the CVM threat model and enables verifiable execution-location guarantees for privacy-sensitive workloads.

cs.CR↗

arXiv2025

Arbitrage with bounded Liquidity

We derive the arbitrage gains or, equivalently, Loss Versus Rebalancing (LVR) for arbitrage between \textit{two imperfectly liquid} markets, extending prior work that assumes the existence of an infinitely liquid reference market. Our result highlights that the LVR depends on the relative liquidity and relative trading volume of the two markets between which arbitrage gains are extracted. Our model assumes that trading costs on at least one of the markets is quadratic. This assumption holds well in practice, with the exception of highly liquid major pairs on centralized exchanges, for which we discuss extensions to other cost functions.

q-fin.MF↗

arXiv2023

Mempool Privacy: An Economic Perspective

A growing body of literature is aimed at designing private mempools in blockchains. The ultimate goal of this research is addressing several phenomena broadly classed under MEV with sandwich attacks as the canonical example. The literature has primarily viewed MEV as a problem arising from oversights in distributed systems and cryptographic protocol design and has attempted to address it with the standard tool sets from those disciplines. This paper argues that the impact of private mempools on markets and agent incentives renders analyses that do not consider the economic lens incomplete. The paper presents several observations across blockchains and traditional finance to justify this argument and highlight specific dynamics for future study.

cs.CR↗