SearcharxivSearch

arXiv · 2501.17732

Gateways for Institutional-Grade Commerce and Interoperability of Digital Assets

Abstract

It is time for the legacy financial infrastructure to seamlessly connect with modern, decentralized infrastructure. Although it is increasingly evident that decentralized infrastructure for finance (namely distributed ledgers) will coexist with and complement legacy infrastructure, it is also clear that such interoperability efforts carry new risks and concerns. In particular, managing the range of heterogeneous (and not well-established) infrastructure brings security, privacy, and regulatory issues. The first step to overcome some of these challenges is to recognize that in many deployment instances using distributed ledgers, the purpose of the ledger is to share resources among the community members. The second step after recognizing that borders exist is to understand that interoperability across systems can be best achieved through the use of standardized service interfaces (or application programming interfaces (API)). In this paper we use the term ledger gateways (or simply gateways) to denote the computer and software systems that implement the standardized service interfaces into a distributed ledger. The main purpose of a gateway is to communicate with other peer gateways that implement the same standardized service interface. Among others, peer gateways perform the transfer of data and value across borders (legal or national borders). Gateways also become a mechanism to manage a permissioned environment, where abiding by laws and regulations is crucial for business compliance (e.g., EU General Data Protection Regulations (GDPR), EU MiCa regulation on digital assets, FAFT Recommendation 15, ISO 27001.

Explore related subjects

Keep this discovery

BibTeXRIS

Rafael Belchior, Thomas Hardjono, Alex Chiriac, Venkatraman Ranakrishna. 2025-01-29. Gateways for Institutional-Grade Commerce and Interoperability of Digital Assets. https://arxiv.org/abs/2501.17732

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

KEEP EXPLORING

Related papers

Online Treasure Hunt in Vertex-Permuted Dynamic Rings

We study the problem of treasure hunt by a group of $k \geq 1$ agents in vertex-permuted dynamic rings (VP). In this model, the $n$ vertices remain on a ring but are permuted at each time step. We first show that treasure hunt is impossible for any $k \leq n-3$ agents, if there are no restrictions on the sequence of permutations used in the dynamic ring. We then study the $VP(\delta)$ setting, in which for every pair $i, j$ of vertices, the edge $(i, j)$ is guaranteed to appear within $\delta$ steps. We show that the class $VP(\delta)$ is feasible only for $\delta \geq \left\lceil \frac{n-1}{2}\right\rceil$. For the one-agent case, we show a tight bound of $\Theta(\delta n)$ on the worst-case search time as well as competitive ratio of any online algorithm for treasure hunt, provided $\delta \geq 2n$. We then give an optimal algorithm for $k$ agents, thereby showing that $k$ agents can obtain a speedup of $k$ on the worst-case search time. Finally, in the R-VP setting, in which in every step, the vertices are arranged as a ring according to a random permutation, we show that treasure hunt takes expected $\Theta(n)$ steps against an oblivious adversary and $\Theta(n \log n)$ steps against an adaptive adversary.

cs.DC

The Computing Channel: How Modulation Programs the Airwaves

Distributed computing and distributed artificial intelligence require frequent exchanges of intermediate results, although many applications need only an aggregate rather than messages from individual devices. Conventional systems recover each message before computing the aggregate, whereas over-the-air computation (OAC) exploits simultaneous transmission to obtain it directly. However, dominant OAC implementations rely on analog signaling, creating a mismatch with finite-precision data and digital communication procedures. This article presents digital function-oriented communication, in which finite-alphabet symbol representations and receiver decisions are jointly designed so that multiple-access superposition encodes the desired function without recovering individual inputs. We introduce its computational-constellation principle, main design approaches, extensions, and implementation challenges. Federated edge learning illustrates how the framework can reduce user-dependent data-bearing resources while operating directly on quantized model updates.

cs.DC

Can AI Remediate Backend Failures Safely? GuardedAct with Blast-Radius-Aware Sandboxing

Large Language Models (LLMs) have shown promising capabilities in generating remediation actions for microservice failures. However, directly executing AI-generated repair actions in production risks cascading collateral damage. We propose GuardedAct, a sandbox-first remediation framework that interposes a blast-radius-aware verification layer between the LLM action generator and the production environment. GuardedAct operates in four phases: (1) ingesting a diagnosis report together with the live system topology and recent telemetry, (2) prompting an LLM to produce a ranked list of candidate remediation actions, (3) simulating each action in a lightweight digital-twin sandbox that estimates the blast radius and assigns a risk label, and (4) enforcing a rollback-confidence gate that auto-executes only low-risk actions while escalating high-risk ones for human review. We evaluate GuardedAct on five fault scenarios injected into the DeathStarBench social-network application. Experimental results show that GuardedAct achieves an overall recovery rate of 87.4% while reducing collateral damage by 79.7% relative to direct LLM execution (from 25.6% to 5.2%), at the cost of a modest sandbox-induced increase in mean time to recovery (approximately 8 s). Ablation studies confirm that each component contributes meaningfully to the safety-speed trade-off.

cs.DC