Covert Networks: How Hard is It to Hide?

TL;DR

This paper investigates the computational complexity of hiding influential users in covert networks using centrality measures, revealing NP-Completeness results and proposing approximation algorithms for the Hiding Leader problem.

Contribution

It proves NP-Completeness of the Hiding Leader problem for core centrality and degree centrality, and introduces a 2-approximation algorithm with hardness bounds.

Findings

NP-Completeness for core centrality with leaders of core value 3

Polynomial-time solvability for degree centrality with bounded degree

A 2-factor approximation algorithm for degree centrality with hardness results

Abstract

Covert networks are social networks that often consist of harmful users. Social Network Analysis (SNA) has played an important role in reducing criminal activities (e.g., counter terrorism) via detecting the influential users in such networks. There are various popular measures to quantify how influential or central any vertex is in a network. As expected, strategic and influential miscreants in covert networks would try to hide herself and her partners (called {\em leaders}) from being detected via these measures by introducing new edges. Waniek et al. show that the corresponding computational problem, called Hiding Leader, is NP-Complete for the degree and closeness centrality measures. We study the popular core centrality measure and show that the problem is NP-Complete even when the core centrality of every leader is only $3$. On the contrary, we prove that the problem becomes polynomial time solvable for the degree centrality measure if the degree of every leader is bounded above by any constant. We then focus on the optimization version of the problem and show that the Hiding Leader problem admits a $2$ factor approximation algorithm for the degree centrality measure. We complement it by proving that one cannot hope to have any $(2-\varepsilon)$ factor approximation algorithm for any constant $\varepsilon>0$ unless there is a $\varepsilon/2$ factor polynomial time algorithm for the Densest $k$-Subgraph problem which would be considered a significant breakthrough.