Attacking Shortest Paths by Cutting Edges

Author:

Miller Benjamin A.1ORCID,Shafi Zohair1ORCID,Ruml Wheeler2ORCID,Vorobeychik Yevgeniy3ORCID,Eliassi-Rad Tina1ORCID,Alfeld Scott4ORCID

Affiliation:

1. Northeastern University, USA

2. University of New Hampshire, USA

3. Washington University in St. Louis, USA

4. Amherst College, USA

Abstract

Identifying shortest paths between nodes in a network is a common graph analysis problem that is important for many applications involving routing of resources. An adversary that can manipulate the graph structure could alter traffic patterns to gain some benefit (e.g., make more money by directing traffic to a toll road). This article presents the Force Path Cut problem, in which an adversary removes edges from a graph to make a particular path the shortest between its terminal nodes. We prove that the optimization version of this problem is APX-hard but introduce PATHATTACK , a polynomial-time approximation algorithm that guarantees a solution within a logarithmic factor of the optimal value. In addition, we introduce the Force Edge Cut and Force Node Cut problems, in which the adversary targets a particular edge or node, respectively, rather than an entire path. We derive a nonconvex optimization formulation for these problems and derive a heuristic algorithm that uses PATHATTACK as a subroutine. We demonstrate all of these algorithms on a diverse set of real and synthetic networks, illustrating where the proposed algorithms provide the greatest improvement over baseline methods.

Funder

United States Air Force

Combat Capabilities Development Command Army Research Laboratory

Under Secretary of Defense for Research and Engineering

Army Research Office

National Science Foundation

Publisher

Association for Computing Machinery (ACM)

Subject

General Computer Science

Reference60 articles.

1. Error and attack tolerance of complex networks

2. The constrained shortest path problem

3. Simplicial closure and higher-order link prediction;Benson Austin R.;Proceedings of the National Academy of Sciences,2018

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