2 citations · 2 across the 1 of their papers we have counts for
6 papers
Strategic Evasion of Centrality Measures
Marcin Waniek, Jan Woźnica, Kai Zhou +3
Among the most fundamental tools for social network analysis are centrality measures, which quantify the importance of every node in the network. This centrality analysis typically…
Blocking Adversarial Influence in Social Networks
Feiran Jia, Kai Zhou, Charles Kamhoua +1
While social networks are widely used as a media for information diffusion, attackers can also strategically employ analytical tools, such as influence maximization, to maximize th…
Robust Collective Classification against Structural Attacks
Kai Zhou, Yevgeniy Vorobeychik
Collective learning methods exploit relations among data points to enhance classification performance. However, such relations, represented as edges in the underlying graphical mod…
Adversarial Robustness of Similarity-Based Link Prediction
Kai Zhou, Tomasz P. Michalak, Yevgeniy Vorobeychik
Link prediction is one of the fundamental problems in social network analysis. A common set of techniques for link prediction rely on similarity metrics which use the topology of t…
Attacking Similarity-Based Link Prediction in Social Networks
Kai Zhou, Tomasz P. Michalak, Talal Rahwan +2
Link prediction is one of the fundamental problems in computational social science. A particularly common means to predict existence of unobserved links is via structural similarit…
Attack Tolerance of Link Prediction Algorithms: How to Hide Your Relations in a Social Network
Marcin Waniek, Kai Zhou, Yevgeniy Vorobeychik +3
Link prediction is one of the fundamental research problems in network analysis. Intuitively, it involves identifying the edges that are most likely to be added to a given network,…