Evidence map›Paper›PMID 42663733›Full record

ArticleNeuroinformatics2026

Cognitive Sovereignty: An AI-Aware Governance Framework for Neural Data Threats, Autonomous Cyber Defense, and Identity-Aware Security in Neurotechnology Systems.

Ms Kritika

Abstract read
PubMed Publisher
In one paragraph

Article in Neuroinformatics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Ms KritikaIndependent Researcher (Neuro-cybersecurity), New Delhi, India. kritikaa2297@yahoo.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Artificial IntelligenceBrain-Computer InterfacesCognitionComputer SecurityHumansAdversarial machine learningAgentic AI securityAI-driven neural threat mitigationBrain-computer interface securityCognitive sovereigntyCybersecurity regulationIdentity-aware authenticationNeural data governanceNeuro-cybersecurity policyNeurorights

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.