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Semi-supervised approach for detecting distributed denial of service in SD-honeypot network environment

The work proposes integrating a honeypot sensor with a software-defined network (SDN) and classifying distributed denial-of-service attacks via semi-supervised learning, combining a pseudo-labelling model based on a support vector machine with subsequent classification using Adaptive Boosting. The evaluation reported by the authors uses monitoring data from the Suricata sensor and examines accuracy, precision, recall, CPU usage, and flow-rule mitigation times.

HoneypotNetwork

What we know

The work proposes integrating a honeypot sensor with a software-defined network (SDN) and classifying distributed denial-of-service attacks via semi-supervised learning, combining a pseudo-labelling model based on a support vector machine with subsequent classification using Adaptive Boosting. The evaluation reported by the authors uses monitoring data from the Suricata sensor and examines accuracy, precision, recall, CPU usage, and flow-rule mitigation times.

Evidence limits

Review limited to the Crossref-deposited abstract; full text was not accessed and results were not independently validated.

Reviewed: author abstract. Full-text results were not analyzed.

Sources and provenance

  1. Semi-supervised approach for detecting distributed denial of service in SD-honeypot network environment
    abstract · 2026-10-11

Reviewed: 2026-10-13. This record may change when new evidence is found.

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