# E-SAWM: A Semantic Analysis-Based ODF Watermarking Algorithm for Edge Cloud Scenarios
## 2 Related Work  
### Application of Edge Computing in the Domain of Financial Data Protection  
Since 2015, edge cloud computing has emerged as a prominent technology, positioned on the Gartner technology maturity curve and experiencing rapid industrialization and growth. Edge computing represents a distributed computing paradigm that positionsprimary processing and data storage at the edge nodes of the network. According to the Edge Computing Industry Alliance [4], it is an open platform integrating network, computing, storage, and application core capabilities at the edge of the network, in close proximity to the data source. This setup enables the provision of intelligent edge services to meet crucial requirements for industrial digitization, including agile connectivity, real-time services, data optimization, application intelligence, and security and privacy protection. International standards organization ETSI [5] defines edge computing as the provisioning of IT service environments and computing capabilities at the network edge, aiming to reduce latency in network operations and service delivery, ultimately enhancing the user experience. Infrastructure for edge cloud computing encompasses various elements, such as distributed IDCs, carrier communication network edge infrastructure, and edge devices like edge-side client nodes, along with their corresponding network environments. Serving as an extension of cloud computing, edge cloud computing provides localized computing capabilities and excels in small-scale, real-time intelligent analytics [6]. These inherent characteristics make it highly suitable for smart applications, where it can effectively support small-scale smart analytics and deliver localized services. In terms of network resources, edge cloud computing assumes the responsibility for data in close proximity to the information source. By facilitating local storage and processing of data, it eliminates the need to upload all data to the cloud [7]. Consequently, this technology significantly reduces the network burden and substantially improves the efficiency of network bandwidth utilization. In application scenarios that prioritize data security, especially in sectors such as finance, edge clouds offer enhanced compliance with stringent security requirements. By enabling the storage and processing of sensitive data locally, edge clouds effectively mitigate the heightened risks of data leakage associated with placing such critical information in uncontrollable cloud environments. In the evolving landscape of the financial industry, there is a paradigm shift toward open banking, often referred to as banking 4.0. Departing from the traditional customer-centric approach, open banking places emphasis on user centricity and advocates for data sharing facilitated by technical channels such as APIs and SDKs. Its primary goal is to foster deeper collaboration and forge stronger business connections between banks and third-party institutions, which enables the seamless integration of financial services into customers' daily lives and production scenarios. The overarching objective is to optimize the allocation of financial resources, enhance service efficiency, and cultivate mutually beneficial partnerships among multiple stakeholders. An illustrative example of this paradigm shift is evident in bank card electronic payment systems, where the deployment of secure and encrypted POS machines at the edge enables convenient electronic payments [8]. Extensive research has been conducted to address the security challenges in edge cloud environments. [PERSON] et al. [9] proposed an enhanced cloud security solution to enhance data protection against attacks. Similarly, [PERSON] et al. [10] proposed a heterogeneous endpoint access authentication mechanism for a three-tier system (\"cloud-edge-end\") in edge computing scenarios, which aimed to support a large number of endpoint authentication requests while ensuring the privacy of endpoint devices. Building upon this, [PERSON] et al.