Security in Cognitive Radio Networks: Threats and Mitigation
Source: University of Maryland
This paper describes a new class of attacks specific to cognitive radio networks. Wireless devices that can learn from their environment can also be taught things by malicious elements of their environment. By putting artificial intelligence in charge of wireless network devices, the authors are allowing unanticipated, emergent behavior, fitting a perhaps distorted or manipulated level of optimality. The state space for a cognitive radio is made up of a variety of learned beliefs and current sensor inputs. By manipulating radio sensor inputs, an adversary can affect the beliefs of a radio, and consequently its behavior.