KIM SANGWOOK 金相旭

… Alternative Names

金相旭キムサンウック

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Researcher Number	00826878
Other IDs
Affiliation (Current)	2025: 神戸大学, 工学研究科, 工学研究科研究員
Affiliation (based on the past Project Information) *help	2023: 神戸大学, 工学研究科, 工学研究科研究員 2021 – 2022: 神戸大学, 工学研究科, 助教 2019: 神戸大学, 工学研究科, 助教
Review Section/Research Field	Except Principal Investigator Basic Section 60070:Information security-related / Medium-sized Section 60:Information science, computer engineering, and related fields / Soft computing
Keywords	Except Principal Investigator 深層学習 / サイバーセキュリティ / 機械学習 / 悪性JavaScript検知 / 攻撃生成過程 / 攻撃検知 / 敵対的サンプル攻撃 / 攻撃生成モデル / 悪性ドメイン検知 / Webセキュリティ … More / IoTセキュリティ / 攻撃観測 / ドメイン知識 / DoS攻撃 / ウェブ媒介型攻撃 / 攻撃生成過程モデル / 悪性サイト検知 / t-SNE / DDoS攻撃検知 / ニューラルネット / SVM / Mirai / DDoS判定 / ダークネット / サイバー攻撃 / 異常検出 / データマイニング / 異常検知 / 可視化 / ダークネット分析 / 広域観測 / 連想ルールマイニング / IoTマルウェア / サイバー攻撃検知 / 相関ルールマイニング / 追加学習 / 攻撃可視化 / 攻撃分類 Less

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
Modelling Attack Generation Process by Introducing Machine Learning and Domain Knowledge and Its Verification for Real Attack Data
- Principal Investigator
  
  小澤誠一
- Project Period (FY)
  2021 – 2024
- Research Category
  
  Grant-in-Aid for Scientific Research (B)
- Review Section
  
  Basic Section 60070:Information security-related
- Research Institution
  Kobe University
Online Learning Algorithms for Real-time Detection, Classification, and Visualization of Cyberattacks
- Principal Investigator
  
  Ozawa Seiichi
- Project Period (FY)
  2016 – 2019
- Research Category
  
  Grant-in-Aid for Scientific Research (B)
- Research Field
  
  Soft computing
- Research Institution
  Kobe University

All 2022 2021 2020 2019 2018 2016

All Journal Article Presentation

[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
[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
[Journal Article] Deep Neural Networks for Malicious JavaScript Detection Using Bytecode Sequences2020
- Author(s)
  Muhammad Fakhrur Rozi, Sangwook Kim and Seiichi Ozawa
- Journal Title
  
  Proc. of 2020 IEEE/INNS International Joint Conference on Neural Networks
  
  Volume: - Pages: 1-8
- Peer Reviewed
- Data Source
  KAKENHI-PROJECT-16H02874
[Journal Article] A machine learning approach to detection of JavaScript-based attacks using AST features and paragraph vectors2019
- Author(s)
  Ndichu Samuel、Kim Sangwook、Ozawa Seiichi、Misu Takeshi、Makishima Kazuo
- Journal Title
  
  Applied Soft Computing
  
  Volume: 84 Pages: 105721-105721
- DOI
  10.1016/j.asoc.2019.105721
- NAID
  120006811119
- Peer Reviewed / Open Access
- Data Source
  KAKENHI-PROJECT-16H02874
[Journal Article] Privacy-Preserving Naive Bayes Classification Using Fully Homomorphic Encryption2018
- Author(s)
  Kim Sangwook、Omori Masahiro、Hayashi Takuya、Omori Toshiaki、Wang Lihua、Ozawa Seiichi
- Journal Title
  
  ICONIP 2018- 25th International Conference on Neural Information Processing
  
  Volume: LNCS11304 Pages: 349-358
- DOI
  10.1007/978-3-030-04212-7_30
- ISBN
  9783030042110, 9783030042127
- Peer Reviewed / Open Access
- Data Source
  KAKENHI-PROJECT-15K00028, KAKENHI-PROJECT-16H02874
[Journal Article] A Fast Online Learning Algorithm of Radial Basis Function Network with Locality Sensitive Hashing2016
- Author(s)
  Siti Hajar Aminah Ali, Kiminori Fukase, Seiichi Ozawa
- Journal Title
  
  Evolving Systems
  
  Volume: 7 Issue: 3 Pages: 173-186
- DOI
  10.1007/s12530-015-9141-5
- NAID
  120005997118
- Peer Reviewed
- Data Source
  KAKENHI-PROJECT-16H02874
[Presentation] HTMLタグの構造に着目したグラフ畳み込みネットワークによる悪性サイト判定2021
- Author(s)
  山本貴巳, Kim Sangwook, 班涛, 高橋健志, 小澤誠一
- Organizer
  コンピュータセキュリティシンポジウム 2021
- 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-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
[Presentation] HTMLタグの構造に着目したグラフ畳み込みネットワークによる悪性サイト判定2021
- Author(s)
  山本貴巳, Kim Sangwook, 班涛, 高橋健志, 小澤誠一
- Organizer
  コンピュータセキュリティシンポジウム 2021
- Data Source
  KAKENHI-PROJECT-21KK0178
[Presentation] A Machine Learning Model Performance Improvement Approach to Detection of Obfuscated JavaScript-based Attacks2020
- Author(s)
  Samuel Ndichu, Sangwook Kim, Seiichi Ozawa
- Organizer
  The Network and Distributed System Security Symposium 2020
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-16H02874
[Presentation] Malicious JavaScript Detection Using Doc2Vec Feature Learning - Improvement in Detection of Obfuscated Parts through Simplification and Decoding2019
- Author(s)
  Samuel Ndichu, Sangwook Kim, Seiichi Ozawa
- Organizer
  The 14th International Workshop on Security 2019
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-16H02874
[Presentation] Privacy-Preserving Naive Bayes Classifier based on Homomorphic Encryption2018
- Author(s)
  Sangwook Kim, Toshiaki Omori, Masahiro Omori, Takuya Hayashi, Lihua Wang, Seiichi Ozawa
- Organizer
  The 13th International Workshop on Security
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-16H02874
[Presentation] Detection of JavaScript-based Attacks Using Doc2Vec Feature Learning2018
- Author(s)
  Samuel Ndichu, Sangwook Kim, Seiichi Ozawa, Misu Takeshi, Kazuo Makishima
- Organizer
  The 13th International Workshop on Security
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-16H02874

1. Ozawa Seiichi (70214129)

# of Collaborated Projects: 3 results

# of Collaborated Products: 13 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. 北園淳 (00733677)

# of Collaborated Projects: 1 results

# of Collaborated Products: 0 results
5. 大森敏明 (10391898)

# of Collaborated Projects: 1 results

# of Collaborated Products: 1 results
6. 白石善明 (70351567)

# of Collaborated Projects: 1 results

# of Collaborated Products: 0 results
7. WANG Licheng

# of Collaborated Projects: 0 results

# of Collaborated Products: 1 results
8. 王立華

# of Collaborated Projects: 0 results

# of Collaborated Products: 1 results

KIM SANGWOOK 金 相旭

金 相旭 キム サンウック

Research Projects

Research Products

Co-Researchers

Refinement of Cyberattack Generation Process Model by Using Machine Learning and Domain Knowledge

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

Modelling Attack Generation Process by Introducing Machine Learning and Domain Knowledge and Its Verification for Real Attack Data

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

Online Learning Algorithms for Real-time Detection, Classification, and Visualization of Cyberattacks

Principal Investigator

Project Period (FY)

Research Category

Research Field

Research Institution

[Journal Article] Understanding the Influence of AST-JS for Improving Malicious Webpage Detection2022

Author(s)

Journal Title

DOI

Data Source

[Journal Article] JStrack: Enriching Malicious JavaScript Detection Based on AST Graph Analysis and Attention Mechanism2021

Author(s)

Journal Title

DOI

ISBN

Data Source

[Journal Article] Deep Neural Networks for Malicious JavaScript Detection Using Bytecode Sequences2020

Author(s)

Journal Title

Data Source

[Journal Article] A machine learning approach to detection of JavaScript-based attacks using AST features and paragraph vectors2019

Author(s)

Journal Title

DOI

NAID

Data Source

[Journal Article] Privacy-Preserving Naive Bayes Classification Using Fully Homomorphic Encryption2018

Author(s)

Journal Title

DOI

ISBN

Data Source

[Journal Article] A Fast Online Learning Algorithm of Radial Basis Function Network with Locality Sensitive Hashing2016

Author(s)

Journal Title

DOI

NAID

Data Source

[Presentation] HTMLタグの構造に着目したグラフ畳み込みネットワークによる悪性サイト判定2021

Author(s)

Organizer

Data Source

[Presentation] Detecting Malicious Websites Based onJavaScript Content Analysis2021

Author(s)

Organizer

Data Source

[Presentation] Detecting Malicious Websites Based onJavaScript Content Analysis2021

Author(s)

Organizer

Data Source

[Presentation] HTMLタグの構造に着目したグラフ畳み込みネットワークによる悪性サイト判定2021

Author(s)

Organizer

Data Source

[Presentation] A Machine Learning Model Performance Improvement Approach to Detection of Obfuscated JavaScript-based Attacks2020

Author(s)

Organizer

Data Source

[Presentation] Malicious JavaScript Detection Using Doc2Vec Feature Learning - Improvement in Detection of Obfuscated Parts through Simplification and Decoding2019

Author(s)

Organizer

Data Source

KIM SANGWOOK 金相旭

金相旭キムサンウック