Proliferation of smartphones enables interaction among nearby users anywhere, anytime. Despite that these interaction opportunities may provide benefit to users, they also involve risks since nearby users may not be known. In this thesis, we propose a decentralized stereotypical trust model that supports variation in human behavior based on context changes, specifically place. We leverage previous studies that show how the place of interaction affects the level of trust of users and applied them to a stereotypical trust scheme. Our results show that the proposed scheme not only performs faster in terms of stereotypes creation time (average 200%) but also reduces the rate of regarding a malicious user as a trustworthy one (average 75%) when com-pared to existing approach.