Abstract
This paper introduces the Better Hide Communities (BHC) benchmark dataset, purposefully crafted for gauging the efficacy of current and prospective community deception algorithms. BHC facilitates the evaluation of algorithmic performance in identifying the best set of updates to apply to a network to hide a target community from community detection algorithms. We believe that BHC will help in advancing the development of community deception algorithms and in promoting a deeper understanding of algorithmic capabilities in applying deceptive practices within communities.
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This work was partially supported by MUR under PRIN project HypeKG Prot. 2022Y34XNM, CUP H53D23003710006; PNRR MUR project PE0000013-FAIR, Spoke 9 - WP9.2.
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Fionda, V. (2024). Better Hide Communities: Benchmarking Community Deception Algorithms. In: Cherifi, H., Rocha, L.M., Cherifi, C., Donduran, M. (eds) Complex Networks & Their Applications XII. COMPLEX NETWORKS 2023. Studies in Computational Intelligence, vol 1144. Springer, Cham. https://doi.org/10.1007/978-3-031-53503-1_31
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