From Community Detection to Community Deception

Abstract

The community deception problem is about how to hide a target community C from community detection algorithms. The need for deception emerges whenever a group of entities (e.g., activists, police enforcements) want to cooperate while concealing their existence as a community. In this paper we introduce and formalize the community deception problem. To solve this problem, we describe algorithms that carefully rewire the connections of C's members. We experimentally show how several existing community detection algorithms can be deceived, and quantify the level of deception by introducing a deception score. We believe that our study is intriguing since, while showing how deception can be realized it raises awareness for the design of novel detection algorithms robust to deception techniques.

References in corpus (7)

• Fast unfolding of communities in large networks
• Modularity and community structure in networks
• Finding community structure in networks using the eigenvectors of matrices
• Near linear time algorithm to detect community structures in large-scale networks
• Statistical Mechanics of Community Detection
• Benchmarks for testing community detection algorithms on directed and weighted graphs with overlapping communities
• Empirical Comparison of Algorithms for Network Community Detection