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Optimized Placement of Security Controllers for Enhancing Intrusion Detection and Resilience in Software-Defined IoT Networks

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Abstract

This study investigates the optimal placement of security controllers in Software-Defined IoT (SD-IoT) networks to enhance intrusion detection and improve network resilience against cyber threats. In SD-IoT environments, the strategic positioning of security controllers plays a vital role in monitoring malicious activity and responding to attacks effectively. However, inefficient controller placement can increase detection time, heighten vulnerability, and degrade overall network performance. To address this challenge, we propose multi-objective optimization approach based on the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) to determine the optimal number and locations of security controllers. The proposed method simultaneously considers network topology, resource constraints, and the characteristics of potential attack patterns to minimize intrusion detection delay, reduce the impact of threats on data transmission, and enhance load distribution. For evaluation, simulations were conducted using topologies from the Internet Topology Zoo. The proposed method was compared against other existing methods, such as Random Placement, Greedy Algorithm and Iterated Local Search strategies, in terms of controllers required, security, latency, load balancing, and deployment cost. Results demonstrate that our approach significantly outperforms other methods, for instance achieving approximately a 60% reduction in deployment cost in the large-scale Cogentco topology. These findings highlight the effectiveness of integrating NSGA-II for strategic controller placement to strengthen security and operational efficiency in SD-IoT networks.

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No datasets were generated or analysed during the current study.

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Funding

This research was partially supported by Grant PID2022-136476OB-I00 funded by MICIU/AEI/10.13039/501100011033/FEDER EU, ERDF/EU, and Gobierno de Aragón (reference group T31_20R).

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Authors and Affiliations

  1. Department of Computer Engineering, University of Mazandaran (UMZ), Babolsar, Iran

    Ali Abdi Seyedkolaei

  2. School of Engineering and Architecture (EINA), Aragon Engineering Research Institute (I3A), University of Zaragoza (UNIZAR), Saragossa, Spain

    José García

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  1. Ali Abdi Seyedkolaei
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  2. José García
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Contributions

Conceptualization, Ali Abdi Seyedkolaei and José García; Data curation, Ali Abdi Seyedkolaei; Formal analysis, Ali Abdi Seyedkolaei and José García; Funding ac-quisition, José García; Investigation, Ali Abdi Seyedkolaei and José García; Methodology, Ali Abdi Seyedkolaei and José García; Software, Ali Abdi Seyedkolaei and José García; Supervision, José García; Validation, Ali Abdi Seyedkolaei and José García; Visualization, Ali Abdi Seyedkolaei and José García; Writing – original draft, Ali Abdi Seyedkolaei; Writing – review & editing, Ali Abdi Seyedkolaei and José García.

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Correspondence to Ali Abdi Seyedkolaei or José García.

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Abdi Seyedkolaei, A., García, J. Optimized Placement of Security Controllers for Enhancing Intrusion Detection and Resilience in Software-Defined IoT Networks. J Netw Syst Manage 34, 110 (2026). https://doi.org/10.1007/s10922-026-10062-5

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