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Rozi Muhammad Fakhrur  Rozi MuhammadFakhrur

ORCIDConnect your ORCID iD *help
… Alternative Names

Rozi MuhammadFakhrur  ロジ ムハマド・ファクル

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Researcher Number 20997382
Other IDs
Affiliation (Current) 2026: 国立研究開発法人情報通信研究機構, サイバーセキュリティ研究所AIセキュリティ研究センター, 研究員
Affiliation (based on the past Project Information) *help 2024: 国立研究開発法人情報通信研究機構, サイバーセキュリティ研究所, 研究員
Review Section/Research Field
Except Principal Investigator
Medium-sized Section 60:Information science, computer engineering, and related fields / Basic Section 60070:Information security-related
Keywords
Except Principal Investigator
深層学習 / 悪性JavaScript検知 / IoTセキュリティ / 攻撃生成過程 / ドメイン知識 / 機械学習 / サイバーセキュリティ / 悪性サイト検知 / DoS攻撃 / 攻撃エコシステム … More / 連合学習AIセキュリティ / ウェブ媒介型攻撃 / 攻撃生成過程モデル / サイバー攻撃 / 敵対的サンプル攻撃 / 攻撃生成モデル / 悪性ドメイン検知 / サイバーセキュリティ」 / Webセキュリティ / 攻撃観測 / 攻撃検知 Less
  • Research Projects

    (2 results)
  • Research Products

    (6 results)
  • Co-Researchers

    (5 People)
  •  Modelling Attack Generation Process by Introducing Machine Learning and Domain Knowledge and Its Verification for Real Attack Data

    • Principal Investigator
      Ozawa Seiichi
    • Project Period (FY)
      2024
    • Research Category
      Grant-in-Aid for Scientific Research (B)
    • Review Section
      Basic Section 60070:Information security-related
    • Research Institution
      Kobe University
  •  Refinement of Cyberattack Generation Process Model by Using Machine Learning and Domain Knowledge

    • Principal Investigator
      小澤 誠一
    • Project Period (FY)
      2021 – 2026
    • Research Category
      Fund for the Promotion of Joint International Research (Fostering Joint International Research (B))
    • Review Section
      Medium-sized Section 60:Information science, computer engineering, and related fields
    • Research Institution
      Kobe University

All 2024 2023 2022 2021

All Journal Article Presentation

  • [Journal Article] Securing Code With Context: Enhancing Vulnerability Detection Through Contextualized Graph Representations2024

    • Author(s)
      Rozi Muhammad Fakhrur、Ban Tao、Ozawa Seiichi、Yamada Akira、Takahashi Takeshi、Inoue Daisuke
    • Journal Title

      IEEE Access

      Volume: 12 Pages: 142101-142126

    • DOI

      10.1109/access.2024.3467180

    • Peer Reviewed / Open Access
    • Data Source
      KAKENHI-PROJECT-23K21670, KAKENHI-PROJECT-21KK0178
  • [Journal Article] Detecting Malicious JavaScript Using Structure-Based Analysis of Graph Representation2023

    • Author(s)
      Rozi Muhammad Fakhrur、Ban Tao、Ozawa Seiichi、Yamada Akira、Takahashi Takeshi、Kim Sangwook、Inoue Daisuke
    • Journal Title

      IEEE Access

      Volume: 11 Pages: 102727-102745

    • DOI

      10.1109/access.2023.3317266

    • Peer Reviewed / Open Access
    • Data Source
      KAKENHI-PROJECT-23K21670
  • [Journal Article] Understanding the Influence of AST-JS for Improving Malicious Webpage Detection2022

    • Author(s)
      Rozi Muhammad Fakhrur、Ozawa Seiichi、Ban Tao、Kim Sangwook、Takahashi Takeshi、Inoue Daisuke
    • Journal Title

      Applied Sciences

      Volume: 12 Issue: 24 Pages: 12916-12916

    • DOI

      10.3390/app122412916

    • Peer Reviewed / Open Access
    • Data Source
      KAKENHI-PROJECT-23K21670, KAKENHI-PROJECT-21KK0178
  • [Journal Article] JStrack: Enriching Malicious JavaScript Detection Based on AST Graph Analysis and Attention Mechanism2021

    • Author(s)
      Rozi Muhammad Fakhrur、Ban Tao、Ozawa Seiichi、Kim Sangwook、Takahashi Takeshi、Inoue Daisuke
    • Journal Title

      Neural Information Processing. ICONIP 2021. Lecture Notes in Computer Science, Springer, Cham

      Volume: 13109 Pages: 669-680

    • DOI

      10.1007/978-3-030-92270-2_57

    • ISBN
      9783030922696, 9783030922702
    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-21KK0178, KAKENHI-PROJECT-23K21670
  • [Presentation] Detecting Malicious Websites Based onJavaScript Content Analysis2021

    • Author(s)
      Muhammad Fakhrur Rozi, Tao Ban, Sangwook Kim, Seiichi Ozawa, Takeshi Takahashi, Daisuke Inoue
    • Organizer
      Computer Security Symposium 2021(CSS2021)
    • Data Source
      KAKENHI-PROJECT-23K21670
  • [Presentation] Detecting Malicious Websites Based onJavaScript Content Analysis2021

    • Author(s)
      Muhammad Fakhrur Rozi, Tao Ban, Sangwook Kim, Seiichi Ozawa, Takeshi Takahashi, Daisuke Inoue
    • Organizer
      Computer Security Symposium 2021(CSS2021)
    • Data Source
      KAKENHI-PROJECT-21KK0178
  • 1.  Ozawa Seiichi (70214129)
    # of Collaborated Projects: 2 results
    # of Collaborated Products: 6 results
  • 2.  吉岡 克成 (60415841)
    # of Collaborated Projects: 2 results
    # of Collaborated Products: 0 results
  • 3.  班 涛 (80462878)
    # of Collaborated Projects: 2 results
    # of Collaborated Products: 6 results
  • 4.  金 相旭 (00826878)
    # of Collaborated Projects: 2 results
    # of Collaborated Products: 5 results
  • 5.  白石 善明 (70351567)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results

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