
Research Article
Cross-Jurisdictional Compliance Barriers and Security Dilemma in Data Flow: A Comparative Study Across the Taiwan Strait
@INPROCEEDINGS{10.1007/978-3-032-43712-9_13, author={Cheng-yong Liu and Cheng Chen}, title={Cross-Jurisdictional Compliance Barriers and Security Dilemma in Data Flow: A Comparative Study Across the Taiwan Strait}, proceedings={Smart Grid and Internet of Things. 10th EAI International Conference, SGIoT 2026, Taichung, Taiwan, November 21--22, 2026, Proceedings}, proceedings_a={SGIOT}, year={2026}, month={11}, keywords={Data Flow Compliance Barriers Cross-Strait Relations}, doi={10.1007/978-3-032-43712-9_13} }- Cheng-yong Liu
Cheng Chen
Year: 2026
Cross-Jurisdictional Compliance Barriers and Security Dilemma in Data Flow: A Comparative Study Across the Taiwan Strait
SGIOT
Springer
DOI: 10.1007/978-3-032-43712-9_13
Abstract
The deepening collaboration between the two sides of the Taiwan Strait in smart manufacturing and smart energy has rendered cross-border data flow an unavoidable imperative. However, the fundamental divergence in logical starting points between Mainland China’s data export control system, centered on “security assessment – localized storage,” and Taiwan, China’s “principle of permission with conditional restrictions” model, modeled on the EU GDPR, is forming a set of intractable compliance barriers. Employing a normative comparative method, this paper dissects the data export regimes on both sides, identifying the operational mechanisms of three layers of obstacles: mutually exclusive export procedures, incommensurable definitions of sensitivity, and asymmetric enforcement intensity. Further, this paper introduces the concept of the “security dilemma” from international politics into the field of data governance, revealing how regulatory escalations undertaken in the name of security, within a context lacking mutual trust and dialogue, undermine the collective security resilience of regional critical infrastructure. To address this dilemma, the main body of the paper proposes a three-pronged solution: “technological buffering, institutional piloting, and experiential benchmarking.” At the technological level, it promotes the application of privacy-enhancing technologies centered on federated learning and homomorphic encryption. Institutionally, it designs a pilot scheme for mutual recognition of sectoral Data Protection Impact Assessments. Comparatively, drawing on the EU-Japan adequacy decisions, it proposes a phased model for limited mutual recognition across the Strait. The article ultimately recommends launching pilots in low-sensitivity sectors such as smart energy and academic healthcare, and provides phased implementation steps.

