Search arXivSearch

arXiv · 2607.13832

Reveal, Correct, Then Pay: Encrypted Mempools and Perpetual Funding Security

Abstract

Encrypted mempools are designed to hide transaction contents until execution order is fixed, preventing many victim dependent forms of maximal extractable value. This paper studies a different class of attack in the form of self-authored state manipulation, in which the attacker knows its own transaction and owns a downstream claim on the state that transaction changes. Perpetual futures funding is a canonical example. The funding signal determines a transfer rate, while receiving side open interest is the transfer base. In a commit then reveal mempool, an adaptive corrective transaction cannot enter the already committed batch. Privacy can therefore create an economic reaction gap even when cryptographic decryption overhead is negligible. We microfound correction through executable arbitrage opportunities. Correctors choose order size against local price impact and inventory cost, while the protocol information schedule determines which opportunities are actionable. The ordering barrier removes ordinary adaptive searchers from the closed stage. It therefore yields a closed stage correction rate below the adaptive correction rate whenever positive adaptive capacity becomes available after reveal. The distortion entering a funding window is multiplied by an explicit response factor. Transaction privacy can also reduce capitalization of predictable funding into entry prices, producing a second amplification channel. The resulting local security index separates attacker blindness, correction shielding, and capitalization shielding.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Benjamin Marsh. 2026-07-15. Reveal, Correct, Then Pay: Encrypted Mempools and Perpetual Funding Security. https://arxiv.org/abs/2607.13832

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

MIRANDA: short signatures from a leakage-free full-domain-hash scheme

We present $\mathsf{Miranda}$, the first family of full-domain-hash signatures based on matrix codes. This signature scheme fulfils the paradigm of Gentry, Peikert and Vaikuntanathan ($\mathsf{GPV}$), which gives strong security guarantees. Our trapdoor is very simple and generic: if we propose it with matrix codes, it can actually be instantiated in many other ways since it only involves a subcode of a decodable code (or lattice) in a unique decoding regime of parameters. Though $\mathsf{Miranda}$ signing algorithm relies on a decoding task where there is exactly one solution, there are many possible signatures given a message to sign and we ensure that signatures are not leaking information on their underlying trapdoor by means of a very simple procedure involving the drawing of a small number of uniform bits. In particular $\mathsf{Miranda}$ does not use a rejection sampling procedure which makes its implementation a very simple task contrary to other $\mathsf{GPV}$-like signatures schemes such as $\mathsf{Falcon}$ or even $\mathsf{Wave}$. We instantiate $\mathsf{Miranda}$ with the famous family of Gabidulin codes represented as spaces of matrices and we study thoroughly its security (in the EUF-CMA security model). For~$128$ bits of classical security, the signature sizes are as low as~$90$ bytes and the public key sizes are in the order of~$2.6$ megabytes.

cs.CR

SteganoBackdoor: Evading Data-Poisoning Defenses via Steganographic Backdoors

Transformer-based models are highly susceptible to backdoor attacks via supervised fine-tuning (SFT). To red-team existing data-poisoning defenses, prior work has increasingly focused on stylized triggers, synthetic artifacts, and token-level perturbations designed to evade detection. However, this trend has shifted threat models away from naturally occurring semantic triggers and realistic low-budget poisoning settings. Addressing this gap, we introduce SteganoBackdoor, an optimization-based framework that transforms semantic-trigger seeds through autoregressive token replacement, sequentially minimizing embedding overlap with the inference-time trigger while preserving a strong per-sample training-time payload. The resulting SteganoPoisons maintain linguistic fluency and encode the payload across ordinary tokens, such that no individual token carries a concentrated signal and the full payload instead emerges from their exact combination and ordering. Across 18 encoder-based and decoder-only models spanning 120M to 14B parameters, SteganoBackdoor achieves high attack success under sub-percent poisoning budgets and exposes limitations in existing data-poisoning defenses.

cs.CR

Foundations and Design Principles of Lightweight Cryptography for IoT Systems

The successful deployment of the Internet of Things (IoT) applications relies heavily on their robust security, and lightweight cryptography is considered an emerging solution in this context. While existing surveys have been examining lightweight cryptographic techniques from the perspective of hardware and software implementations or performance evaluation, there is a significant gap in addressing different security aspects, such as design principles, specific to the IoT environment. This study aims to bridge this gap. This research presents an examination with focusing on the security evaluation of symmetric lightweight ciphers commonly used in IoT systems. The objective of this study is to provide a concise overview of lightweight ciphers with emphasizing on their security challenges which is an essential consideration for real-time and resource-constrained applications.

cs.CR