  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.
