SIAISOC-PHSep 1, 2016

From Community Detection to Community Deception

arXiv:1609.00149v15 citations
Originality Incremental advance
AI Analysis

This addresses the need for groups like activists or police to conceal their community structure, though it is incremental as it builds on existing detection methods.

The paper tackles the problem of hiding a target community from detection algorithms by rewiring connections, and experimentally demonstrates deception across several algorithms with a quantified deception score.

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.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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