From Discipline-Oriented to Competency-Based: Research on a "Broad-Spectrum and In-Depth" Training Model for High-Level Talents in Cyberspace Security
Authors:
Yan Liu, Xiaoyu Guo, Ruixiang Li
Keywords:
Cyberspace Security, Talent Training, Competency-Based, Broad-Spectrum and In-Depth, Research-Application Synergy.
Doi:
10.70114/ahmer.2026.5.1.P70
Abstract
With the formal establishment of cyberspace as the "fifth domain" following land, sea, air, and space, the training of cybersecurity talents has evolved from a mere focus on technical education to a critical component of national security strategy. However, current graduate education remains constrained by traditional discipline-oriented linear models, facing triple challenges of skill supply-demand mismatch, the paradox of broad employment prospects versus narrow research fields, and a lack of ethical awareness in the era of artificial intelligence. This paper proposes a shift towards a competency-based approach, constructing a "broad-spectrum and in-depth" training model for high-level talents. By establishing a flexible knowledge base, an ecosystem of research-application synergy embedded throughout the entire chain, and a layered cognitive defense system, the aim is to cultivate compound security experts with a solid foundation, practical sharpness, and clear ethical boundaries to address increasingly complex national security challenges.