为脑机接口设计隐私保护分级框架，防范神经数据泄露风险
Revisiting Privacy Preservation in Brain-Computer Interfaces: Conceptual Boundaries, Risk Pathways, and a Protection-Strength Grading Framework
- 构建三维隐私保护框架，按对象、阶段、强度分级
- 揭示神经数据在全生命周期中的重识别风险路径
- 强调去除无关敏感信息，兼顾实用性和伦理安全
脑机接口（BCI）正从实验室走向临床与现实应用。根据ISO/IEC 8663:2025标准，BCI是中枢神经系统活动与外部软硬件系统的直接通信链路。该链路带来的隐私风险不仅限于原始神经信号泄露，还包括神经数据、衍生表征、模型资产及解码输出在采集、传输、存储、训练、推理和反馈等环节被重新关联到个体，或用于推断超出任务所需的信息。本文从通用BCI范式出发，界定隐私保护边界、保护对象，厘清用户数据隐私与模型隐私在共享风险路径中的关系。提出一个三维分类框架——保护对象、生命周期阶段、主导保护强度等级，将现有工作划分为四个保护强度层级。最后，将心理隐私与神经伦理风险列为开放问题，强调隐私保护不应仅隐藏数据，还应剥离任务无关的敏感信息，同时保持下游任务可用性。
原文摘要 · Abstract (English)
Brain-computer interfaces (BCIs) are moving rapidly from laboratory research into clinical, edge, and real-world settings. Under ISO/IEC 8663:2025, a BCI is a direct communication link between central nervous system activity and external software or hardware systems. This link expands privacy risk beyond raw neural-signal leakage: neural data, derived representations, model assets, and decoded outputs can be re-associated with individuals across collection, transmission, storage, training, inference, and feedback, or used to infer information beyond what a task requires. Starting from the general BCI paradigm, this review deffnes privacy-protection boundaries, protection objects, and the relationship between user data privacy and model privacy within a shared risk pathway. It then proposes a three-dimensional framework - protection object, lifecycle stage, and dominant protection-strength level - to classify existing work into four levels of protection strength. Finally, mental privacy and neuroethical risks are treated as open issues, emphasizing that BCI privacy protection should not only obscure data but also disentangle task-irrelevant sensitive information while preserving downstream utility. Keywords: Brain-computer interface, Neural data privacy, User data privacy, Model privacy, Disentanglement of task-irrelevant sensitive information, Protection-strength grading, Neuroethical risks
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