In wireless sensor networks, adversaries can make use of the traffic information to locate the monitored objects, e.g., to hunt endangered animals or kill soldiers. In this paper, we first define a hotspot phenomenon that causes an obvious inconsistency in the network traffic pattern due to the large volume of packets originating from a small area. Second, we develop a realistic adversary model, assuming that the adversary can monitor the network traffic in multiple areas, rather than the entire network or only one area. Using this model, we introduce a novel attack called Hotspot-Locating where the adversary uses traffic analysis techniques to locate hotspots. Finally, we propose a cloud-based scheme for efficiently protecting source nodes' location privacy against Hotspot-Locating attack by creating a cloud with an irregular shape of fake traffic, to counteract the inconsistency in the traffic pattern and camouflage the source node in the nodes forming the cloud. To reduce the energy cost, clouds are active only during data transmission and the intersection of clouds creates a larger merged cloud, to reduce the number of fake packets and also boost privacy preservation. Simulation and analytical results demonstrate that our scheme can provide stronger privacy protection than routing-based schemes and requires much less energy than global-adversary-based schemes.