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by IQAC KIITKIIT Deemed to be University — Internal Quality Assurance Cell

Publication2025

A Unified Benchmark of Boosting and Tree-Based Models for Flow-Based Network Intrusion Detection

The record

Type
Publication
Date
1 January 2025
Level
National
Journal
Proceedings 2025 IEEE 3rd International Symposium on Sustainable Energy Signal Processing and Cybersecurity Isssc 2025
Published
1 January 2025
DOI
10.1109/isssc66652.2025.11387947
Scopus ID
105034993167
Authors
4
Open access
No
Citations
0
International co-authorship
No
Co-author countries
IN

Classification

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UN Sustainable Development Goals

  1. 16.4 Significantly reduce illicit financial and arms flows and combat all forms of organized crime

    TargetPrimaryHigh confidenceJudged

    Boosting and tree-based machine learning models benchmark flow-based network intrusion detection achieving greater than 98% accuracy

    High confidence
    The subject matter is a strong and direct inference from the record type, the funding or organising body, or the programme context, even where the title alone is thin. Example: an ICMR-funded project against SDG 3, on the strength of the agency.
    Judged
    Judged against the published classification rubric, under the rubric and prompt versions recorded with the run that produced it.
    Produced by
    claude-haiku-4-5-20251001, under kortex-publication-v1

Viksit Bharat @2047

  1. vb-4.4 Public safety, cybersecurity and national security

    Sub-themePrimaryHigh confidenceJudged

    Cybersecurity technology enhancement preventing criminal activity through automated intrusion detection

    Produced by
    claude-haiku-4-5-20251001, under kortex-publication-v1

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KIIT Deemed to be University. “A Unified Benchmark of Boosting and Tree-Based Models for Flow-Based Network Intrusion Detection”. Kortex.

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