Conceptual Design and Application of a Defense Big Data Early Warning System Based on the DIME Analytical Framework: A Study on Response Models to Contemporary Security Threats

This paper presents a conceptual design and application of a defense big data early warning system based on the DIME (Diplomacy, Information, Military, Economy) analytical framework to address contemporary complex and multidimensional security threats. By systematically collecting and integrating key variables derived from the diplomatic, informational, military, and economic domains, the study develops a threat prediction model capable of detecting potential security risks at an early stage. Through an empirical case analysis, the validity of the DIME-based approach is verified, demonstrating its effectiveness in identifying diverse security risk signals, including military threats. However, limitations such as data bias and predictive uncertainty remain, indicating that effective domestic implementation requires institutional and technical support, including the establishment of inter-agency data-sharing mechanisms and the continuous enhancement of big data analytics infrastructure.