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Updated: Sep 9, 2025

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機械学習とディープラーニングでサイバーセキュリティに革命をもたらすためにデータ分析を活用する

Asadi Srinivasulu1,2, Tae-Hoon Kim3, Ravikumar Chinthaginjala4

  • 1Cooperative Research centre for contamination Assessment and Remediation of the Environment (CRC CARE),Global Centre for Environmental Remediation/College of Engineering Science & Environment, ATC Building, The University of New Castle, Callaghan, NSW2308, Australia. srinuasadi@gmail.com.

Scientific reports
|August 29, 2025
PubMed
まとめ

この研究では,コンボリューションニューラルネットワーク (CNN) を使用してサイバーセキュリティのデータを分析し,脅威の検出と分類において高い精度を達成しています. このディープラーニングのアプローチは 進化するサイバー攻撃に対するサイバーセキュリティの防御を強化します

キーワード:
アノマリー検出人工知能コンボリューションニューラルネットワーク (CNN)サイバー防衛サイバーセキュリティサイバー 脅威サイバーセキュリティインシデント対応データ分析ディープラーニング情報セキュリティ侵入検知機械学習ネットワークのセキュリティパターン認識合成データ脅威検出

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