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                <identifier>oai:data.mendeley.com/88p4xh8td9.1</identifier>
                <datestamp>2026-03-04T15:19:25Z</datestamp>
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            <metadata><oai_dc:dc xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
    <dc:creator>Dam Minh, Linh</dc:creator>
    <dc:title>FW-Flow: A curated multi-class firewall flow dataset with engineered flow-based and statistical features</dc:title>
    <dc:publisher>Mendeley Data</dc:publisher>
    <dc:description>The dataset is derived from the publicly available Internet Firewall Data dataset provided by the UCI Machine Learning Repository (DOI: 10.24432/C5131M). The original data were collected from internet traffic records on a university firewall and comprise 65,532 multi-class labeled flow records.
  - FW-Flow provides a curated and feature-engineered version of the data, including the original 12 raw firewall attributes (ports, NAT mappings, bytes, packets, elapsed time) together with 30 additional flow-based, behavioral, and statistical derived features, resulting in 42 structured attributes.
  - The dataset supports multi-class classification (allow, deny, drop, reset-both), anomaly detection, and traffic behavior modeling research.
  - Approximately 43% of flows exhibit zero-second duration due to logging granularity in the original records. A small epsilon value (1e-6) was applied during rate-based feature computation to ensure numerical stability.
All preprocessing and feature engineering procedures are fully reproducible via the accompanying scripts.

[1] Internet Firewall Data [Dataset], UCI Machine Learning Repository, 2019. DOI: 10.24432/C5131M.</dc:description>
    <dc:subject>Computer Science</dc:subject>
    <dc:subject>Network Security</dc:subject>
    <dc:subject>Machine Learning</dc:subject>
    <dc:subject>Intrusion Detection</dc:subject>
    <dc:contributor id="https://orcid.org/0009-0003-0400-5175">Han Minh, Chau</dc:contributor>
    <dc:contributor id="https://orcid.org/0009-0001-1698-2673">Tran Cong, Hung</dc:contributor>
    <dc:type>Dataset</dc:type>
    <dc:identifier>doi:10.17632/88p4xh8td9.1</dc:identifier>
    <dc:identifier>oai:data.mendeley.com/88p4xh8td9.1</dc:identifier>
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    <dc:date>2026-03-04T15:19:25Z</dc:date>
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