Cognitive Sovereignty: An AI-Aware Governance Framework for Neural Data Threats, Autonomous Cyber Defense, and...

Neural data collected using brain-computer interfaces, neural implants, and emotion detection systems is analyzed by AI classifiers and agentic architectures to serve purposes such as authentication, access control, and behavioral inference, however, there exists no comprehensive, binding cybersecurity or data protection regime to regulate such neural data. The regulations that currently exist i.e., GDPR, HIPAA, the Budapest Convention, the 2025 UNESCO Recommendation on Neurotechnology Ethics, and a small number of state laws (e.g., Colorado 2024, California SB 1223, Montana, Connecticut) create a fragmented and incomplete emerging framework rather than no framework at all. In this paper, the author propose Cognitive Sovereignty architecture, an approach of governance through the combination of a legally recognized definition and technical parameters defining neural data as a new class of data which necessitates specific regulatory, adversarially sound processing frameworks, and jurisdictionally agnostic enforcement mechanisms. By conducting comparative law research, threat modeling based on STRIDE model and governance modeling, this paper highlights structural issues with the existing regimes and suggests a framework composed of Declaration on Cognitive Sovereignty, neuro-cybercrime protocol of the Budapest Convention, and AI layer-specific compliance requirements based on NIST AI RMF and the EU AI Act.