Community Deception in Networks: Where We Are and Where We Should Go

Community deception tackles the following problem: given a target community C inside a network G and a budget of updates β (e.g., edge removal and additions), what is the best way (i.e., optimization of some function ϕG(C) ) to perform such updates in a way that C can escape to a detector D (i.e., a community detection algorithm)? This paper aims at: (i) presenting an analysis of the state-of-the-art deception techniques; (ii) evaluating state-of-the-art deception techniques: (iii) making available a library of techniques to practitioners and researchers.