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A New Type of Anomaly Detection Problem in Dynamic Graphs: An Ant Colony Optimization Approach

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Bioinspired Optimization Methods and Their Applications (BIOMA 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13627))

Abstract

Anomaly detection has gained great attention in complex network analysis. Every unusual behavior in a complex system can be viewed as an anomaly. In this article, we propose a new anomaly type in dynamic graphs, an existing community-based anomaly detection problem combined with the heaviest k-subgraph problem. Searching the heaviest subgraphs in dynamic graphs viewed as an anomaly problem can give new insights into the studied dynamic networks. An ant colony optimization algorithm is proposed for the heaviest k-subgraph problem and used for the community detection problem. Numerical experiments on real-world dynamic networks are conducted, and the results show the importance of the proposed problem and the potential of the solution method.

This work was supported by a grant of the Ministry of Research, Innovation and Digitization, CNCS/CCCDI - UEFISCDI, project number 194/2021 within PNCDI III.

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Correspondence to Noémi Gaskó .

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Tasnádi, Z., Gaskó, N. (2022). A New Type of Anomaly Detection Problem in Dynamic Graphs: An Ant Colony Optimization Approach. In: Mernik, M., Eftimov, T., Črepinšek, M. (eds) Bioinspired Optimization Methods and Their Applications. BIOMA 2022. Lecture Notes in Computer Science, vol 13627. Springer, Cham. https://doi.org/10.1007/978-3-031-21094-5_4

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  • DOI: https://doi.org/10.1007/978-3-031-21094-5_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-21093-8

  • Online ISBN: 978-3-031-21094-5

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