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2021 | OriginalPaper | Chapter

PATHATTACK: Attacking Shortest Paths in Complex Networks

Authors : Benjamin A. Miller, Zohair Shafi, Wheeler Ruml, Yevgeniy Vorobeychik, Tina Eliassi-Rad, Scott Alfeld

Published in: Machine Learning and Knowledge Discovery in Databases. Research Track

Publisher: Springer International Publishing

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Abstract

Shortest paths in complex networks play key roles in many applications. Examples include routing packets in a computer network, routing traffic on a transportation network, and inferring semantic distances between concepts on the World Wide Web. An adversary with the capability to perturb the graph might make the shortest path between two nodes route traffic through advantageous portions of the graph (e.g., a toll road he owns). In this paper, we introduce the Force Path Cut problem, in which there is a specific route the adversary wants to promote by removing a low-cost set of edges in the graph. We show that Force Path Cut is NP-complete. It can be recast as an instance of the Weighted Set Cover problem, enabling the use of approximation algorithms. The size of the universe for the set cover problem is potentially factorial in the number of nodes. To overcome this hurdle, we propose the PATHATTACK algorithm, which via constraint generation considers only a small subset of paths—at most 5% of the number of edges in 99% of our experiments. Across a diverse set of synthetic and real networks, the linear programming formulation of Weighted Set Cover yields the optimal solution in over 98% of cases. We also demonstrate running time vs. cost tradeoff using two approximation algorithms and greedy baseline methods. This work expands the area of adversarial graph mining beyond recent work on node classification and embedding.

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Appendix
Available only for authorised users
Footnotes
1
The eigenscore of an edge is the product of the entries in the principal eigenvector of the adjacency matrix corresponding to the edge’s vertices.
 
2
This alternative method of selecting the destination was used due to the computational expense of identifying successive shortest paths in large grid-like networks.
 
4
GreedyEigenscore only outperforms GreedyCost in COMP with uniform weights.
 
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Metadata
Title
PATHATTACK: Attacking Shortest Paths in Complex Networks
Authors
Benjamin A. Miller
Zohair Shafi
Wheeler Ruml
Yevgeniy Vorobeychik
Tina Eliassi-Rad
Scott Alfeld
Copyright Year
2021
DOI
https://doi.org/10.1007/978-3-030-86520-7_33

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