隨著資訊技術的快速發展，如大數據的氾濫、網絡安全問題日益突
出等，保險行業在數據管理和存儲方面面臨著挑戰。區塊鏈和 IPFS 等分佈式文件系統等新興技術為保險業提供了創新解決方案。本文旨在探索IPFS 和區塊鏈在保險領域的應用，特別關注基於數據重要性和規模的數據存儲解決方案決策。我們首先介紹 IPFS 和區塊鏈的基本概念和特性，然後深入討論它們在保險行業的用例。我們著重介紹如何利用 IPFS 和區塊鏈設計和實現數據存儲解決方案，根據數據以及環境的因素選擇最合適的存儲方式。我們探索了不同的評估指標和演算法，並提出了一個數據存儲決策框架。我們還討論了與 IPFS 和區塊鏈相關的安全和隱私注意事項，以及潛在的解決方案。通過研究和實驗，我們評估不同方法在存儲成本、性能和可擴展性方面的有效性，並提供建議和未來方向。
根據我們的研究，我們得出結論，IPFS 和區塊鏈為保險業提供了創
新的數據存儲解決方案，可以根據上傳當下的環境因素以及數據大小和過去修改次數進行決策，並提供高效、安全和可靠的數據管理。此類解決方案可以幫助保險公司降低成本、優化數據處理工作流程並增強數據的可訪問性和完整性。我們還指出了當前架構面臨的局限性，包括技術複雜性、實際應用和合規性要求，這些都需要進一步研究和實踐探索。

With the rapid development of information technology, such as the proliferation of big data and increasingly prominent network security issues, the insurance industry is facing challenges in data management and storage.
Emerging technologies such as blockchain and distributed file systems such as IPFS offer innovative solutions for the insurance industry. This article aims to explore the application of IPFS and blockchain in the insurance sector, with a particular focus on data storage solution decisions based on data importance and scale. We first introduce the basic concepts and features of IPFS and blockchain, and then discuss in depth their use cases in the insurance industry. We focus on how to use IPFS and blockchain to design and implement data storage solutions, and choose the most appropriate storage method based on data and environmental factors. We explore different evaluation metrics and algorithms and propose a data storage decision-making framework. We also discuss security and privacy considerations related to IPFS and blockchain, as well as potential solutions. Through research and experiments, we evaluate the effectiveness of different approaches in terms of storage cost, performance, and scalability and provide recommendations and future directions.
Based on our research, we conclude that IPFS and blockchain provide the insurance industry with innovative data storage solutions that can make decisions based on environmental factors at the time of uploading as well as data size and past modification times, and provide efficient, secure and Reliable data management. Such solutions can help insurers reduce costs, optimize data processing workflows, and enhance data accessibility and integrity. We also point out the limitations faced by current architectures, including technical complexity, practical applications, and compliance requirements, which require further research and practical exploration.

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