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A new approach to combine multiplex networks and time series attributes: Building intrusion detection systems (IDS) in cybersecurity

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  • Iglesias Pérez, Sergio
  • Moral-Rubio, Santiago
  • Criado, Regino

Abstract

Intrusion Detection Systems (IDS) are fundamental tools in cybersecurity environments. In this paper, we present a new methodology for the creation of intrusion detection systems (IDS) based on a strategy that combines the use of multiplex networks and time series analysis to provide a probability that an IP address be an attacker in a certain time. This approach reduces the number of alerts to a small number of IP addresses as well as the computation effort by not having to analyze each event independently. The evaluation of all traffic happens only at pre-defined times. The methodology relies on both the original utilization of some unsupervised machine learning techniques and on the use of certain time series attributes and their representation as a complex multiplex network, achieving a very significant reduction in the dimensionality of the resulting data representation. The result is a very effective intrusion detection system in large corporate environments and a new approach in the representation of the analyzed data as shown in the real case presented.

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  • Iglesias Pérez, Sergio & Moral-Rubio, Santiago & Criado, Regino, 2021. "A new approach to combine multiplex networks and time series attributes: Building intrusion detection systems (IDS) in cybersecurity," Chaos, Solitons & Fractals, Elsevier, vol. 150(C).
    • Handle: RePEc:eee:chsofr:v:150:y:2021:i:c:s0960077921004975
    DOI: 10.1016/j.chaos.2021.111143
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    References listed on IDEAS

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    Cited by:

    1. Pérez, Sergio Iglesias & Moral-Rubio, Santiago & Criado, Regino, 2023. "Combining multiplex networks and time series: A new way to optimize real estate forecasting in New York using cab rides," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).
    2. Sergio Iglesias Perez & Regino Criado, 2022. "Increasing the Effectiveness of Network Intrusion Detection Systems (NIDSs) by Using Multiplex Networks and Visibility Graphs," Mathematics, MDPI, vol. 11(1), pages 1-24, December.
    3. Contreras-Aso, Gonzalo & Criado, Regino & Vera de Salas, Guillermo & Yang, Jinling, 2023. "Detecting communities in higher-order networks by using their derivative graphs," Chaos, Solitons & Fractals, Elsevier, vol. 177(C).
    4. Iglesias-Perez, Sergio & Criado, Regino, 2023. "Temporal metagraph: A new mathematical approach to capture temporal dependencies and interactions between different entities over time," Chaos, Solitons & Fractals, Elsevier, vol. 175(P1).

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