  While link prediction in networks has been a hot topic over the years, its
robustness has not been well discussed in literature. In this paper, we study
the robustness of some mainstream link prediction methods under various kinds
of network attack strategies, including the random attack (RDA), centrality
based attacks (CA), similarity based attacks (SA), and simulated annealing
based attack (SAA). Through the variation of precision, a typical evaluation
index of link prediction, we find that for the SA and SAA, a small fraction of
link removals can significantly reduce the performance of link prediction. In
general, the SAA has the highest attack efficiency, followed by the SA and then
CA. Interestingly, the performance of some particular CA strategies, such as
the betweenness based attacks (BA), are even worse than the RDA. Furthermore,
we discover that a link prediction method with high performance probably has
lower attack robustness, and the vice versa.
