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

Publication2026

Random Forest-Based LR-DDoS Detection in Cloud: Enhanced Preprocessing and Comparative Evaluation

The record

Type
Publication
Date
1 January 2026
Level
National
Journal
1st International Conference on Intelligent Computing Networks and Security IC Icns 2026
Published
1 January 2026
DOI
10.1109/ic-icns68863.2026.11537636
Scopus ID
105042273987
Authors
6
Open access
No
Citations
0
International co-authorship
No
Co-author countries
IN

Classification

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UN Sustainable Development Goals

  1. 16.3 Promote the rule of law at the national and international levels and ensure equal access to justice for all

    TargetPrimaryHigh confidenceJudged

    Random Forest model with enhanced preprocessing pipeline detects low-rate distributed denial-of-service attacks achieving better stability and generalization in cloud systems.

    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

    Cloud security and intrusion detection research supports cybersecurity infrastructure protection.

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

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KIIT Deemed to be University. “Random Forest-Based LR-DDoS Detection in Cloud: Enhanced Preprocessing and Comparative Evaluation”. Kortex.

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