The problem of finding a better immunization strategy for controlling the spreading of the epidemic with limited resources has attracted much attention since its great theoretical significance and wide application. The traditional strategies either neglect the connection of the neighbors or require global information about the network such as degree centrality strategy, betweenness centrality strategy and closeness centrality strategy. In this paper, we propose an ameba immunization strategy which considers the relationship not only between the focal node and its neighbors but also among the neighbors of the focal node. This relationship, denoting as the ability to restrain the spreading of the focal node, indicates that how much dependence the neighbors have on the focal node. The immunized nodes of the networks are those with higher ability. To test the performance of our method, we conduct the experiments on some artificial and real-world networks, via the Susceptible-Infected-Recovered (SIR) simulation. The results show that the proposed method outperforms the existing well-known methods.