Formal Verification for Blockchain-based Insurance Claims Processing
- URL: http://arxiv.org/abs/2402.13169v1
- Date: Tue, 20 Feb 2024 17:29:59 GMT
- Title: Formal Verification for Blockchain-based Insurance Claims Processing
- Abstract summary: Insurance claims processing involves multi-domain entities and multi-source data.
We simulate the formalism on the chaincodes and analyze the breach of chaincodes via model checking.
- Score: 1.8087312035329557
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Insurance claims processing involves multi-domain entities and multi-source data, along with a number of human-agent interactions. Use of Blockchain technology-based platform can significantly improve scalability and response time for processing of claims which are otherwise manually-intensive and time-consuming. However, the chaincodes involved within the processes that issue claims, approve or deny them as required, need to be formally verified to ensure secure and reliable processing of transactions in Blockchain. In this paper, we use a formal modeling approach to verify various processes and their underlying chaincodes relating to different stages in insurance claims processing viz., issuance, approval, denial, and flagging for fraud investigation by using linear temporal logic (LTL). We simulate the formalism on the chaincodes and analyze the breach of chaincodes via model checking.
Related papers
- Formal Verification of Agentic Systems over Operational Data [59.98246281888422]
Agentic systems driven by large language models (LLMs) are increasingly deployed in real-world where they act on persistent operational data.<n>Existing approaches do not provide such system-level guarantees.<n>We study here the verification of agentic systems comprising a single LLM and a tool orchestration harness over relational operational data.
arXiv Detail & Related papers (2026-08-04T13:01:30Z) - Compliance-Aware Agentic Payments on Stablecoin Rails [0.0]
We present a compliance-aware architecture that combines x402-style, signature-based payment authorisation and relayed execution with programmable compliance embedded as an on-chain guardrail.
arXiv Detail & Related papers (2026-04-30T11:15:04Z) - UniDetect: LLM-Driven Universal Fraud Detection across Heterogeneous Blockchains [9.89047849878308]
We introduce UniDetect, a multi-chain cryptocurrency fraud account detection method based on large language models (LLMs)<n>Specifically, we use domain knowledge to guide the LLM to generate general transaction summary texts applicable to heterogeneous blockchain accounts.<n> Experiments on multiple blockchains show that UniDetect outperforms existing methods 5.57% to 7.58% in Kolmogorov-Smirnov (KS)
arXiv Detail & Related papers (2026-04-14T06:04:37Z) - LOCARD: An Agentic Framework for Blockchain Forensics [2.6498598849144464]
We introduce LOCARD, the first agentic framework for blockchain forensics.<n>LOCARD operationalizes this perspective through a Tri-Core Cognitive Architecture.<n>We evaluate LOCARD on the Group-Transfer Tracing task for dismantling Sybil clusters.
arXiv Detail & Related papers (2026-04-05T18:04:50Z) - Towards Verifiably Safe Tool Use for LLM Agents [53.55621104327779]
Large language model (LLM)-based AI agents extend capabilities by enabling access to tools such as data sources, APIs, search engines, code sandboxes, and even other agents.<n>LLMs may invoke unintended tool interactions and introduce risks, such as leaking sensitive data or overwriting critical records.<n>Current approaches to mitigate these risks, such as model-based safeguards, enhance agents' reliability but cannot guarantee system safety.
arXiv Detail & Related papers (2026-01-12T21:31:38Z) - Document Data Matching for Blockchain-Supported Real Estate [2.9873162504735133]
This work presents a system that integrates optical character recognition (OCR), natural language processing (NLP), and verifiable credentials (VCs) to automate document extraction, verification, and management.<n>The approach standardizes heterogeneous document formats into VCs and applies automated data matching to detect inconsistencies, while the blockchain provides a decentralized trust layer that reinforces transparency and integrity.<n>The proposed framework demonstrates the potential to streamline real estate transactions, strengthen stakeholder trust, and enable scalable, secure digital processes.
arXiv Detail & Related papers (2025-12-30T20:30:48Z) - Data Certification Strategies for Blockchain-based Traceability Systems [7.459390431892085]
We consider a typical system for blockchain-based traceability of a production process.<n>We propose and analyze some strategies for certifying the data of such a process on blockchain.
arXiv Detail & Related papers (2025-11-06T14:37:38Z) - Scaling Code-Assisted Chain-of-Thoughts and Instructions for Model Reasoning [65.20602712957725]
Caco is a novel framework that automates the synthesis of high-quality, verifiable, and diverse instruction-CoT reasoning data.<n>Our work establishes a paradigm for building self-sustaining, trustworthy reasoning systems without human intervention.
arXiv Detail & Related papers (2025-10-05T07:59:24Z) - Efficient Blockchain-based Steganography via Backcalculating Generative Adversarial Network [105.47203971578871]
We propose a generic blockchain-based steganography framework (GBSF)<n>The sender generates the required fields such as amount and fees, where the additional covert data is embedded to enhance the channel capacity.<n>Based on GBSF, we design a reversible generative adversarial network (R-GAN)<n>We propose R-GAN with Counter-intuitive data preprocessing and Custom activation functions, namely CCR-GAN.
arXiv Detail & Related papers (2025-06-19T04:43:41Z) - SoK: Concurrency in Blockchain -- A Systematic Literature Review and the Unveiling of a Misconception [3.462869032423588]
Concurrency and parallelism are a double-edged sword.<n>While they improve throughput, they also introduce risks like race conditions, non-determinism, and vulnerabilities such as deadlock and livelock.<n>This paper presents the first survey of smart contracts, offering a systematic literature review organized into key dimensions.
arXiv Detail & Related papers (2025-06-02T17:13:03Z) - Automated Reasoning in Blockchain: Foundations, Applications, and Frontiers [0.0]
decentralization, immutability, and auditability, achieved through distributed consensus algorithms and cryptographic techniques, offer advantages for multi-stakeholder applications requiring transparency and trust.
However, the inherent complexity and security-critical nature of blockchain systems necessitate rigorous analysis and verification to ensure their correctness, reliability, and resilience against potential vulnerabilities.
arXiv Detail & Related papers (2025-03-26T11:48:54Z) - EvoChain: a Recovery Approach for Permissioned Blockchain Applications [7.094737268994282]
This article presents EvoChain, a chaincode framework extension introducing controlled mutability for data redaction and recovery under time-limited or specific conditions.
We validated our approach using WineTracker, a Hyperledger Fabric-based supply chain application.
arXiv Detail & Related papers (2024-11-25T23:02:17Z) - CryptoFormalEval: Integrating LLMs and Formal Verification for Automated Cryptographic Protocol Vulnerability Detection [41.94295877935867]
We introduce a benchmark to assess the ability of Large Language Models to autonomously identify vulnerabilities in new cryptographic protocols.
We created a dataset of novel, flawed, communication protocols and designed a method to automatically verify the vulnerabilities found by the AI agents.
arXiv Detail & Related papers (2024-11-20T14:16:55Z) - Digital Twin-Assisted Federated Learning with Blockchain in Multi-tier Computing Systems [67.14406100332671]
In Industry 4.0 systems, resource-constrained edge devices engage in frequent data interactions.
This paper proposes a digital twin (DT) and federated digital twin (FL) scheme.
The efficacy of our proposed cooperative interference-based FL process has been verified through numerical analysis.
arXiv Detail & Related papers (2024-11-04T17:48:02Z) - BlockFound: Customized blockchain foundation model for anomaly detection [47.04595143348698]
BlockFound is a customized foundation model for anomaly blockchain transaction detection.
We introduce a series of customized designs to model the unique data structure of blockchain transactions.
BlockFound is the only method that successfully detects anomalous transactions on Solana with high accuracy.
arXiv Detail & Related papers (2024-10-05T05:11:34Z) - Scalable Zero-Knowledge Proofs for Verifying Cryptographic Hashing in Blockchain Applications [16.72979347045808]
Zero-knowledge proofs (ZKPs) have emerged as a promising solution to address the scalability challenges in modern blockchain systems.
This study proposes a methodology for generating and verifying ZKPs to ensure the computational integrity of cryptographic hashing.
arXiv Detail & Related papers (2024-07-03T21:19:01Z) - Identifying contributors to supply chain outcomes in a multi-echelon setting: a decentralised approach [47.00450933765504]
We propose the use of explainable artificial intelligence for decentralised computing of estimated contributions to a metric of interest.
This approach mitigates the need to convince supply chain actors to share data, as all computations occur in a decentralised manner.
Results demonstrate the effectiveness of our approach in detecting the source of quality variations compared to a centralised approach.
arXiv Detail & Related papers (2023-07-22T20:03:16Z) - Blockchain Large Language Models [65.7726590159576]
This paper presents a dynamic, real-time approach to detecting anomalous blockchain transactions.
The proposed tool, BlockGPT, generates tracing representations of blockchain activity and trains from scratch a large language model to act as a real-time Intrusion Detection System.
arXiv Detail & Related papers (2023-04-25T11:56:18Z) - Online Safety Property Collection and Refinement for Safe Deep
Reinforcement Learning in Mapless Navigation [79.89605349842569]
We introduce the Collection and Refinement of Online Properties (CROP) framework to design properties at training time.
CROP employs a cost signal to identify unsafe interactions and use them to shape safety properties.
We evaluate our approach in several robotic mapless navigation tasks and demonstrate that the violation metric computed with CROP allows higher returns and lower violations over previous Safe DRL approaches.
arXiv Detail & Related papers (2023-02-13T21:19:36Z) - Towards automated verification of multi-party consensus protocols [0.0]
Hyperledger Fabric framework exposes a multi-party consensus, based on endorsement policy protocol, to reach a consensus on a transaction.
We propose a verification technique of endorsement policies using statistical model checking and hypothesis testing.
One can use our technique to design enterprise applications with the Hyperledger Fabric framework.
arXiv Detail & Related papers (2021-12-04T18:28:59Z) - CoCoMoT: Conformance Checking of Multi-Perspective Processes via SMT
(Extended Version) [62.96267257163426]
We introduce the CoCoMoT (Computing Conformance Modulo Theories) framework.
First, we show how SAT-based encodings studied in the pure control-flow setting can be lifted to our data-aware case.
Second, we introduce a novel preprocessing technique based on a notion of property-preserving clustering.
arXiv Detail & Related papers (2021-03-18T20:22:50Z)
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.