Several methods have been proposed to combat learningattacks [8]. First, the learning results must always be reevaluated
over time. For example, the activities of the primary users in a cognitive radio network should be constantly recomputed
so that the previously learned statistical process of activities of the primary users that may be incorrect will be
abandoned. Second, there should be a truly controlled environment during the learning phases, which means no malicious
signals are present during the learning phase. Third, if the learned action breaks some basic theoretic results, then
this action should not be used. Fourth, cognitive radios can make use of group learning instead of individual learning.
Several secondary users can form a group to learn the environment,and thus the attacker cannot conduct a learning
attack so easily.