In the digital age, cross-border data flows are a key driver of global economic growth. However, this growth is accompanied by mounting security and compliance risks. Although countries are prioritizing data security, the absence of unified, universally binding regulations creates a fragmented and complex governance landscape. This paper systematically reviews trade agreements, domestic laws, and international regulations to define the concept and scope of cross-border data flows. It also introduces a data lifecycle theory adapted for cross-border scenarios. Through a comparative analysis of relevant policies in the European Union, the United States, and China at various stages of the data lifecycle, the paper identifies commonalities and differences. Based on these findings, the paper provides policy recommendations to harmonize global data governance frameworks, strengthen international cooperation, and balance national security concerns with the free flow of data.

In the context of globalization and rapid development of information technology, cross-border flow of data has become an important part of international trade. This paper firstly analyzes the necessity and risk of data cross-border and discusses the relevant legal framework in China. Secondly, this paper, for the first time, uses Petri nets to model the business process of cross-border data flow, effectively and comprehensively describing the steps and interrelationships in the three phases of data transmission: before transmission, during transmission, and overseas maintenance. Finally, the proposed model is simulated and experimented by PIPE software, which verifies the boundedness, security and deadlock-free characteristics of the model, and proves the feasibility and necessity of Petri nets in the application of cross-border business processes of data.

In the context of the information age, promoting digital government and smart cities has made government data sharing a key trend. Given its special nature, securing government data requires an effective security system for safe and efficient management. This paper explores government data security and technical systems, examines China's current data management situation, and compares management strategies in China, the EU, and the US. This paper adopts a data lifecycle-driven security management approach and leverages two widely recognized frameworks to propose a system that balances data openness and security. Finally, we propose an integrated learning method based on BERT and Random Forest, use real data sets to verify the feasibility of data grouping, and promote the integration of government data management and efficient technology.

Energy storage is an important part of the new power system, responsible for ensuring stable power output and balancing loads. At the same time, it is also a national critical infrastructure. As the country gradually strengthens its control over data security risks of critical infrastructure, data security issues in the energy storage industry have become a focus of attention. In this context, this paper collects and organizes and analyzes relevant literature on data security in the energy storage industry. First, the energy storage system and energy storage technology are summarized and analyzed, and the data and data characteristics of the energy storage system are explained. Secondly, the current data security risks of the energy storage system are sorted out, including BMS network security risks, user privacy leakage risks, information interaction risks of distributed energy storage systems, smart meter data leakage risks, and trust risks between devices. Based on the above data security risks, the existing energy storage data security governance methods are sorted and classified. Finally, it is summarized that the current research in the field of data security in the energy storage industry is not sufficient. This paper comprehensively analyzes the literature on data security in the energy storage industry in recent years, which will provide support for the research on data security governance in the energy storage industry.