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, but applied efforts have been relatively 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：近年来神经技术的快速发展，在神经技术与安全领域之间催生出新的关键交叉点。植入式设备、无创监测和无创治疗技术均可能侵犯个体认知的隐私与自主权。越来越多的科学家和医学界人士呼吁应对此问题，但实际应用层面的努力仍相对有限。阻碍认知安全科学工程研究的主要障碍，在于缺乏描述和分析相关问题的清晰手段。本文建立了认知安全这一数学框架，通过借鉴多个领域的方法与研究成果，实现了对上述问题的描述与分析。我们论证了若干对认知安全具有重要意义的统计性质，进而描述了试图侵犯隐私与自主权的攻击者所面临的算法问题，以及试图阻止此类行为的防御者所面临的算法问题。