On April 15, 2025, China’s 10th National Security Education Day, officers from the People’s Procuratorate of Xiayi County, Shangqiu City, Henan Province, lead a national security education session for students at Yucai School in Xiayi County. Photo: IC PHOTO

Contemporary security studies face a range of methodological challenges. As security risks grow increasingly interconnected and cross-domain in nature, traditional paradigms based on singular causal frameworks are proving inadequate for analyzing the emergence and evolution of complex threats. At the same time, while emerging technologies such as artificial intelligence and big data offer novel tools for security analysis, they also introduce new sources of risk—including concerns over algorithmic transparency and data quality. In response, researchers should embrace innovative methods while remaining mindful of cognitive constraints that may stem from technology dependence.

Historical evolution of methodologies

In the aftermath of World War II, “security” replaced “war” and “defense” as the central concept in security studies, marking a shift in focus that expanded the field to encompass a broader array of political issues beyond military affairs. The field’s methodological approaches have since evolved through several distinct stages.

Prior to the end of the Cold War, security studies primarily adopted a state-centric perspective and focused on traditional security issues, employing methods such as case studies and game theory. The behavioral revolution in political science brought a push for greater scientific rigor, leading to the growth of quantitative research and the development of security-related databases. After the Cold War, non-traditional security issues—such as economic, societal, environmental, and food security—gained prominence, and research objects expanded beyond the state to encompass non-state actors and even individuals.

As attention to non-state actors increased, so did the availability of foundational data, accelerating the development of conflict databases and driving innovation in research methods. Techniques such as spatial analysis and experimental methods became widely applied in security studies. Since the beginning of the 21st century, the “emergent” nature of non-traditional security threats and the global spillover effects of war have compelled a shift away from singular causal frameworks toward dynamic, multidimensional complexity analysis. Fueled by breakthroughs in revolutionary technologies such as AI, big data, and quantum computing, security studies is transitioning from “theory-driven” to “data-driven” approaches, giving rise to interdisciplinary methods.

Challenges and future directions

Under the dual impact of globalization and the digital revolution, the limitations of traditional methodologies in security studies have become evident, exposing deeper challenges in the field’s capacity for knowledge production.

Conflict between old and new research paradigms: On one hand, the pursuit of universally valid causal explanations remains one of the ultimate goals of academic security studies. On the other hand, in an increasingly turbulent world, the field also assumes responsibility for addressing real-world problems—a task for which traditional paradigms are increasingly ill-equipped.

Disconnection between disciplinary logic and problem-solving logic: The “de-bordering” and complexity of contemporary security threats necessitate the adoption of more dynamic and cross-domain research methods. While security studies appear to have established an interdisciplinary matrix integrating political science, economics, computer science, and other fields, in reality, this integration often relies on a superficial patchwork of approaches and lacks genuine innovation.

Misalignment between technological advancement and the essence of research: Overreliance on data and emerging technologies could lead to “precise blindness”— where researchers possess vast datasets but lack meaningful insight into the nature of the threats they study. Blind faith in predictive technologies can distort analytical focus, leading the field away from its foundational purpose.

In today’s world, the convergence of emerging security threats and technological revolutions may spur a restructuring of knowledge production paradigms in security studies. New practice-oriented models are better positioned to address pressing real-world issues. In terms of disciplinary boundaries, security studies have already moved beyond their traditional foundations in political science and international relations, with the potential to develop genuinely “transdisciplinary” methodologies and achieve cross-domain knowledge production.

Su Ruolin is an associate professor from the School of International and Public Affairs at Shanghai Jiao Tong University.