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.
Community Deception in Networks: Where We Are and Where We Should Go / Fionda, V.; Pirro', G.. - (2021). (Intervento presentato al convegno 10th International Conference on Complex Networks and their Applications tenutosi a Madrid).
Community Deception in Networks: Where We Are and Where We Should Go
G. Pirro'
2021
Abstract
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.