arXiv subjects

Abhimanyu Nag

Publications and source records attributed to Abhimanyu Nag.

6 recordsLinked to original sources

arXiv2026

SoK: Speedy Secure Finality

While Ethereum has successfully achieved dynamic availability together with safety, a fundamental delay remains between transaction execution and immutable finality. In Ethereum's current Gasper protocol, this latency is on the order of 15 minutes, exposing the network to ex ante reorganization attacks, enabling MEV extraction, and limiting the efficiency of economic settlement. These limitations have motivated a growing body of work on Speedy Secure Finality (SSF), which aims to minimize confirmation latency without weakening formal security guarantees. This paper surveys the state of the art in fast finality protocol design. We introduce the core theoretical primitives underlying this space, including reorganization resilience and the generalized sleepy model, and trace their development from Goldfish to RLMD-GHOST. We then analyze the communication and aggregation bottlenecks faced by single-slot finality protocols in large validator settings. Finally, we survey the 3-slot finality (3SF) protocol as a practical synthesis that balances fast finality with the engineering constraints of the Ethereum network.

cs.CR↗

arXiv2025

On Sybil Proofness in Competitive Combinatorial Exchanges

We study Sybil manipulation in BRACE, a competitive equilibrium mechanism for combinatorial exchanges, by treating identity creation as a finite perturbation of the empirical distribution of reported types. Under standard regularity assumptions on the excess demand map and smoothness of principal utilities, we obtain explicit linear bounds on price and welfare deviations induced by bounded Sybil invasion. Using these bounds, we prove a sharp contrast: strategyproofness in the large holds if and only if each principal's share of identities vanishes, whereas any principal with a persistent positive share can construct deviations yielding strictly positive limiting gains. We further show that the feasibility of BRACE fails in the event of an unbounded population of Sybils and provide a precise cost threshold that ensures disincentivization of such attacks in large markets.

econ.TH↗

arXiv2025

A Coincidence of Wants Mechanism for Swap Trade Execution in Decentralized Exchanges

We propose a mathematically rigorous framework for identifying and completing Coincidence of Wants (CoW) cycles in decentralized exchange (DEX) aggregators. Unlike existing auction based systems such as CoWSwap, our approach introduces an asset matrix formulation that not only verifies feasibility using oracle prices and formal conservation laws but also completes partial CoW cycles of swap orders that are discovered using graph traversal and are settled using imbalance correction. We define bridging orders and show that the resulting execution is slippage free and capital preserving for LPs. Applied to real world Arbitrum swap data, our algorithm demonstrates efficient discovery of CoW cycles and supports the insertion of synthetic orders for atomic cycle closure. This work can be thought of as the detailing of a potential delta-neutral strategy by liquidity providing market makers: a structured CoW cycle execution.

cs.GT↗

arXiv2025

Economic Security of Multiple Shared Security Protocols

As restaking protocols gain adoption across blockchain ecosystems, there is a need for Actively Validated Services (AVSs) to span multiple Shared Security Providers (SSPs). This leads to stake fragmentation which introduces new complications where an adversary may compromise an AVS by targeting its weakest SSP. In this paper, we formalize the Multiple SSP Problem and analyze two architectures : an isolated fragmented model called Model $\mathbb{M}$ and a shared unified model called Model $\mathbb{S}$, through a convex optimization and game-theoretic lens. We derive utility bounds, attack cost conditions, and market equilibrium that describes protocol security for both models. Our results show that while Model $\mathbb{M}$ offers deployment flexibility, it inherits lowest-cost attack vulnerabilities, whereas Model $\mathbb{S}$ achieves tighter security guarantees through single validator sets and aggregated slashing logic. We conclude with future directions of work including an incentive-compatible stake rebalancing allocation in restaking ecosystems.

cs.CR↗

arXiv2024

Multi Agent Influence Diagrams for DeFi Governance

Decentralized Finance (DeFi) governance models have become increasingly complex due to the involvement of numerous independent agents, each with their own incentives and strategies. To effectively analyze these systems, we propose using Multi Agent Influence Diagrams (MAIDs) as a powerful tool for modeling and studying the strategic interactions within DeFi governance. MAIDs allow for a comprehensive representation of the decision-making processes of various agents, capturing the influence of their actions on one another and on the overall governance outcomes. In this paper, we study a simple governance game that approximates real governance protocols and compute the Nash equilibria using MAIDs. We further outline the structure of a MAID in MakerDAO.

cs.GT↗

arXiv2024

Compound V3 Economic Audit Report

Compound Finance is a decentralized lending protocol that enables the secure and efficient borrowing and lending of cryptocurrencies, utilizing smart contracts and dynamic interest rates based on supply and demand to facilitate transactions. The protocol enables users to supply different crypto assets and accrue interest, while borrowers can avail themselves of loans secured by collateralized assets. Our collaboration with Compound Finance focuses on harnessing the power of the Chainrisk simulation engine to optimize risk parameters of the Compound V3 (Comet) protocol. This report delineates a comprehensive methodology aimed at calculating key risk metrics of the protocol. This optimization framework is pivotal for mitigating systemic risks and enhancing the overall stability of the protocol. By leveraging Chainrisk's Cloud Platform, we conduct millions of simulations to evaluate the protocol's Value at Risk (VaR) and Liquidations at Risk (LaR), ultimately providing recommendations for parameter adjustments.

q-fin.RM↗