  Currently the Dempster-Shafer based algorithm and Uniform Random Probability
based algorithm are the preferred method of resolving security games, in which
defenders are able to identify attackers and only strategy remained ambiguous.
However this model is inefficient in situations where resources are limited and
both the identity of the attackers and their strategies are ambiguous. The
intent of this study is to find a more effective algorithm to guide the
defenders in choosing which outside agents with which to cooperate given both
ambiguities. We designed an experiment where defenders were compelled to engage
with outside agents in order to maximize protection of their targets. We
introduced two important notions: the behavior of each agent in target
protection and the tolerance threshold in the target protection process. From
these, we proposed an algorithm that was applied by each defender to determine
the best potential assistant(s) with which to cooperate. Our results showed
that our proposed algorithm is safer than the Dempster-Shafer based algorithm.
