The rapid advancement in neurotechnology in recent years has created an emerging critical intersection between neurotechnology and security. Implantable devices, non-invasive monitoring, and non-invasive therapies all carry with them the prospect of violating the privacy and autonomy of individuals' cognition. A growing number of scientists and physicians have made calls to address this issue -- which we term Cognitive Security -- but applied efforts have been limited. A major barrier hampering scientific and engineering efforts to address Cognitive Security is the lack of a clear means of describing and analyzing relevant problems. In this paper we develop Cognitive Security, a mathematical framework which enables such description and analysis by drawing on methods and results from multiple fields. We demonstrate certain statistical properties which have significant implications for Cognitive Security, and then present descriptions of the algorithmic problems faced by attackers attempting to violate privacy and autonomy, and defenders attempting to obstruct such attempts.

翻译：近年来神经技术的迅猛发展催生了神经技术与安全领域的一个新兴关键交叉点。植入式设备、非侵入式监测和非侵入式治疗均可能侵犯个体认知的隐私与自主性。越来越多的科学家和医生呼吁解决这一问题——我们将其称为认知安全——但实际应用仍十分有限。阻碍认知安全领域科学与工程工作的主要障碍，在于缺乏描述和分析相关问题的清晰手段。本文提出了认知安全这一数学框架，通过融合多学科方法与成果，实现了此类描述与分析。我们论证了某些对认知安全具有重要影响的统计特性，进而描述了试图侵犯隐私与自主性的攻击者，以及试图阻挠此类行为的防御者所面临的算法问题。