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Using honeynet data and a time series to predict the number of cyber attacks

The authors describe using honeynet data and time series to predict SSH attacks, covering overall activity and attacks from specific geographical regions. They apply ARIMA, SARIMA, GARCH and Bootstrapping with real-world data, presenting the viability, precision and usefulness of each approach across areas of IT security.

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What we know

The authors describe using honeynet data and time series to predict SSH attacks, covering overall activity and attacks from specific geographical regions. They apply ARIMA, SARIMA, GARCH and Bootstrapping with real-world data, presenting the viability, precision and usefulness of each approach across areas of IT security.

Evidence limits

Review based only on the abstract deposited with Crossref; the full text was not accessed and results were not independently validated.

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

Sources and provenance

  1. Using honeynet data and a time series to predict the number of cyber attacks
    abstract · 2026-10-11

Reviewed: 2026-10-16. This record may change when new evidence is found.

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