Auditing Blockchain Innovations: Technical Challenges Beyond Traditional Finance
- URL: http://arxiv.org/abs/2603.26361v1
- Date: Fri, 27 Mar 2026 12:41:24 GMT
- Title: Auditing Blockchain Innovations: Technical Challenges Beyond Traditional Finance
- Abstract summary: This paper builds on prior research on a comprehensive framework addressing existence, ownership, valuation, and internal control verification.<n>We demonstrate how autoethnographic methodology becomes necessary for understanding technical complexities that external analysis cannot capture.
- Score: 0.0
- License: http://creativecommons.org/licenses/by-nc-sa/4.0/
- Abstract: Blockchain technology introduces asset types and custody mechanisms that fundamentally break traditional financial auditing paradigms. This paper presents an autoethnographic analysis of cryptoasset auditing challenges, build on top of prior research on a comprehensive framework addressing existence, ownership, valuation, and internal control verification. Drawing from lived experience implementing blockchain systems as an engineer, smart contract auditor, and CTO of a publicly traded cryptoasset firm, we demonstrate how autoethnographic methodology becomes necessary for understanding technical complexities that external analysis cannot capture. Through detailed examination of token airdrops, multi-signature smart contracts, and real-time on-chain reporting, we provide experimental approaches and common scenarios that auditing firms can analyze to address blockchain innovations currently considered technically insurmountable.
Related papers
- GoAT-X: A Graph of Auditing Thoughts for Securing Token Transactions in Cross-Chain Contracts [52.51342355102833]
Cross-chain bridges, the critical infrastructure of the multi-chain ecosystem, have become a primary target for attackers.<n>Existing defenses, such as bytecode-level static analysis, are ill-equipped to handle the semantic complexity of cross-chain interactions.<n>We propose GoAT-X, a framework that shifts automated cross-chain smart contracts auditing from pattern matching toward systematic first-principles verification.
arXiv Detail & Related papers (2026-04-27T11:34:21Z) - SoK: Web3 RegTech for Cryptocurrency VASP AML/CFT Compliance [14.435108642393319]
This paper examines how blockchain-native RegTech solutions leverage distributed ledger properties to enable novel compliance capabilities.<n>We develop three organizing the Web3 RegTech domain: a regulatory paradigm evolution framework across ten dimensions, a compliance protocol taxonomy encompassing five verification layers, and a RegTech lifecycle framework spanning preventive, real-time, and investigative phases.<n>Our analysis reveals critical gaps between academic innovation and industry deployment, alongside persistent challenges in cross-chain tracking, DeFi interaction analysis, privacy protocol monitoring, and scalability.
arXiv Detail & Related papers (2025-12-31T14:31:29Z) - Blockchain Technology: Core Mechanisms, Evolution, and Future Implementation Challenges [0.0]
We examine the core technical components including distributed consensus algorithms, cryptographic principles, and smart contract functionality.<n>We identify critical challenges facing widespread blockchain adoption, including technical limitations, regulatory hurdles, and integration complexities with existing systems.
arXiv Detail & Related papers (2025-05-13T17:50:31Z) - Enhancing Blockchain Cross Chain Interoperability: A Comprehensive Survey [39.613235136790244]
We systematically analyze over 150 high impact sources from academic journals, digital libraries, and grey literature.<n>We offer a classification of interoperability approaches including Atomic Swaps, Sidechains, Light Clients, and so on, which represent the most comprehensive overview to date.<n>Our findings aim to support researchers, policymakers, and industry leaders in harnessing the transformative potential of blockchain interoperability to address current challenges and drive forward a cohesive multi-chain ecosystem.
arXiv Detail & Related papers (2025-05-08T04:24:50Z) - Trusted Compute Units: A Framework for Chained Verifiable Computations [41.94295877935867]
This paper introduces the Trusted Compute Unit (TCU), a unifying framework that enables composable and interoperable computations across heterogeneous technologies.<n>By enabling secure off-chain interactions without incurring on-chain confirmation delays or gas fees, TCUs significantly improve system performance and scalability.
arXiv Detail & Related papers (2025-04-22T09:01:55Z) - Blockchain Data Analysis in the Era of Large-Language Models [21.81035847078574]
Existing blockchain data analysis tools face challenges, including data scarcity, the lack of generalizability, and the lack of reasoning capability.<n>We believe large language models (LLMs) can mitigate these challenges.<n>This paper systematically explores potential techniques and design patterns in LLM-integrated blockchain data analysis.
arXiv Detail & Related papers (2024-12-09T07:32:35Z) - Balancing Confidentiality and Transparency for Blockchain-based Process-Aware Information Systems [43.253676241213626]
We propose an architecture for blockchain-based PAISs to preserve confidentiality and transparency.<n>Smart contracts enact, enforce and store public interactions, while attribute-based encryption techniques are adopted to specify access grants to confidential information.<n>We assess the security of our solution through a systematic threat model analysis and evaluate its practical feasibility.
arXiv Detail & Related papers (2024-12-07T20:18:36Z) - On Replacing Cryptopuzzles with Useful Computation in Blockchain Proof-of-Work Protocols [0.12289361708127873]
Researchers have been pursuing the idea of replacing cryptopuzzles with useful computing tasks for over a decade.
We provide insight into the effect of introducing "usefulness" and of transitioning to task classes other than cryptopuzzles.
We discuss pertinent techniques and present research gaps in the current state-of-the-art.
arXiv Detail & Related papers (2024-04-24T08:49:41Z) - Enhancing Trust and Privacy in Distributed Networks: A Comprehensive Survey on Blockchain-based Federated Learning [51.13534069758711]
Decentralized approaches like blockchain offer a compelling solution by implementing a consensus mechanism among multiple entities.
Federated Learning (FL) enables participants to collaboratively train models while safeguarding data privacy.
This paper investigates the synergy between blockchain's security features and FL's privacy-preserving model training capabilities.
arXiv Detail & Related papers (2024-03-28T07:08:26Z) - Generative AI-enabled Blockchain Networks: Fundamentals, Applications,
and Case Study [73.87110604150315]
Generative Artificial Intelligence (GAI) has emerged as a promising solution to address challenges of blockchain technology.
In this paper, we first introduce GAI techniques, outline their applications, and discuss existing solutions for integrating GAI into blockchains.
arXiv Detail & Related papers (2024-01-28T10:46:17Z) - Detecting Anomalous Cryptocurrency Transactions: an AML/CFT Application
of Machine Learning-based Forensics [5.617291981476445]
The paper analyzes a real-world dataset of Bitcoin transactions represented as a directed graph network through various techniques.
It shows that the neural network types known as Graph Convolutional Networks (GCN) and Graph Attention Networks (GAT) are a promising AML/CFT solution.
arXiv Detail & Related papers (2022-06-07T16:22:55Z) - BlockNet Report: Exploring the Blockchain Skills Concept and Best
Practice Use Cases [0.0]
The project explores the academic and industry landscape of existing initiatives in education which offer courses.
Job descriptions and adverts are analyzed in order to specify today's competence requirements from enterprises.
The analysis of the various use cases will be conducted and defined in a standardized format to identify the key drivers and competence requirements for technology applications.
arXiv Detail & Related papers (2021-02-08T16:40:09Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.