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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence / EAAI-20

Optimal Surveillance of Covert Networks by Minimizing Inverse Geodesic Length

February 1, 2023

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Authors

Serge Gaspers

University of New South Wales


Kamran Najeebullah

University of New South Wales


DOI:

10.1609/aaai.v33i01.3301533


Abstract:

The inverse geodesic length (IGL) is a well-known and widely used measure of network performance. It equals the sum of the inverse distances of all pairs of vertices. In network analysis, IGL of a network is often used to assess and evaluate how well heuristics perform in strengthening or weakening a network. We consider the edge-deletion problem MINIGLED. Formally, given a graph G, a budget k, and a target inverse geodesic length T, the question is whether there exists a subset of edges X with |X| ≤ ck, such that the inverse geodesic length of G − X is at most T.In this paper, we design algorithms and study the complexity of MINIGL-ED. We show that it is NP-complete and cannot be solved in subexponential time even when restricted to bipartite or split graphs assuming the Exponential Time Hypothesis. In terms of parameterized complexity, we consider the problem with respect to various parameters. We show that MINIGL-ED is fixed-parameter tractable for parameter T and vertex cover by modeling the problem as an integer quadratic program. We also provide FPT algorithms parameterized by twin cover and neighborhood diversity combined with the deletion budget k. On the negative side we show that MINIGL-ED is W[1]-hard for parameter tree-width.

Topics: AAAI

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HOW TO CITE:

Serge Gaspers||Kamran Najeebullah Optimal Surveillance of Covert Networks by Minimizing Inverse Geodesic Length Proceedings of the AAAI Conference on Artificial Intelligence (2019) 533-540.

Serge Gaspers||Kamran Najeebullah Optimal Surveillance of Covert Networks by Minimizing Inverse Geodesic Length AAAI 2019, 533-540.

Serge Gaspers||Kamran Najeebullah (2019). Optimal Surveillance of Covert Networks by Minimizing Inverse Geodesic Length. Proceedings of the AAAI Conference on Artificial Intelligence, 533-540.

Serge Gaspers||Kamran Najeebullah. Optimal Surveillance of Covert Networks by Minimizing Inverse Geodesic Length. Proceedings of the AAAI Conference on Artificial Intelligence 2019 p.533-540.

Serge Gaspers||Kamran Najeebullah. 2019. Optimal Surveillance of Covert Networks by Minimizing Inverse Geodesic Length. "Proceedings of the AAAI Conference on Artificial Intelligence". 533-540.

Serge Gaspers||Kamran Najeebullah. (2019) "Optimal Surveillance of Covert Networks by Minimizing Inverse Geodesic Length", Proceedings of the AAAI Conference on Artificial Intelligence, p.533-540

Serge Gaspers||Kamran Najeebullah, "Optimal Surveillance of Covert Networks by Minimizing Inverse Geodesic Length", AAAI, p.533-540, 2019.

Serge Gaspers||Kamran Najeebullah. "Optimal Surveillance of Covert Networks by Minimizing Inverse Geodesic Length". Proceedings of the AAAI Conference on Artificial Intelligence, 2019, p.533-540.

Serge Gaspers||Kamran Najeebullah. "Optimal Surveillance of Covert Networks by Minimizing Inverse Geodesic Length". Proceedings of the AAAI Conference on Artificial Intelligence, (2019): 533-540.

Serge Gaspers||Kamran Najeebullah. Optimal Surveillance of Covert Networks by Minimizing Inverse Geodesic Length. AAAI[Internet]. 2019[cited 2023]; 533-540.


ISSN: 2374-3468


Published by AAAI Press, Palo Alto, California USA
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