Research on Data Security and Privacy Enhancement Mechanisms of AI Large Models in the Context of Low-Altitude Economy

Abstract

The advancement of low-altitude economy as a national strategy and its in-depth integration with AI large models have highlighted the core value of data security and privacy protection. Addressing the issues of inadequate adaptation between existing research technologies and economic management, as well as the neglect of differentiated needs of small and medium-sized enterprises, this paper constructs a "technology-management-economy" collaborative enhancement framework and proposes a full-chain mechanism of "source prevention-process control-backend guarantee-dynamic optimization". Integrating lightweight hierarchical protection, cross-subject governance and scenario-adaptive strategies, the framework achieves a dynamic balance among security, efficiency and cost. Empirical verification based on 12 low-altitude logistics enterprises shows that the mechanism can reduce the risk of privacy leakage to 0.08%, cut compliance costs by 35%, and increase training data coverage to 92%. This research provides gradient solutions for subjects of different scales, improves the theoretical system of low-altitude economy data governance, and offers practical support for the high-quality development of the industry.