Updated on 2024/11/21

写真a

 
Kobayashi Satoru
 
Organization
Faculty of Environmental, Life, Natural Science and Technology Assistant Professor
Position
Assistant Professor
External link

Degree

  • Ph.D. in Information Science and Technology ( 2018.3   The University of Tokyo )

Research Areas

  • Informatics / Information network

Research History

  • Okayama University   Fuculty of Environmental, Life, Natural Science and Technology   Assistant Professor

    2023.4

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    Country:Japan

    Notes:(所属部局名の変更)

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  • Okayama University   Fuculty of Natural Science and Technology   Assistant Professor

    2022.10 - 2023.3

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    Country:Japan

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  • National Institute of Informatics   Information Systems Architecture Science Research Division   Project Researcher

    2018.4 - 2022.9

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Professional Memberships

 

Papers

  • Effectiveness of MAC Systems based on LSM and their Security Policy Configuration for Protecting IoT Devices Reviewed

    Masato Miki, Toshihiro Yamauchi, Satoru Kobayashi

    Journal of Internet Services and Information Security   14 ( 3 )   293 - 315   2024.8

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    Language:English   Publishing type:Research paper (scientific journal)   Publisher:SASA Publications  

    The number of attacks exploiting Internet of Things (IoT) devices has been increasing with the emergence of IoT malware targeting IoT devices. The use of IoT devices in a wide variety of situations has resulted in an urgent need to improve the security of the IoT devices themselves. However, the IoT devices themselves have low hardware performance and their operating systems and applications are not frequently updated, leaving many devices vulnerable to IoT malware attacks. Mandatory Access Control (MAC) systems based on Linux Security Modules (LSM), such as SELinux and AppArmor, can mitigate the impact of these attacks, even if software vulnerabilities are discovered and exploited. However, most IoT devices do not currently employ these systems. While existing approaches have examined on-board resources as one factor affecting the applicability of MAC systems, they are insufficient to address all relevant factors. In this paper, we report the factors that may prevent the deployment of LSM-based secure OS in IoT devices and the results of our evaluation of the effectiveness of LSM-based secure OS against IoT malware attacks. First, we comprehensively investigated the impact of each factor of IoT devices on the deployment of LSM-based secure OS. To improve the comprehensiveness of the factors affecting the deployment, we investigated the kernel version, CPU architecture, and BusyBox support. Next, we conducted an attack experiment that simulated the attack method of Mirai, a typical IoT malware, to investigate whether it is possible to protect against IoT malware. We also showed how to modify the security policy, and the cost of modifying it, for secure OSs that cannot prevent attacks from IoT malware with the default security policy. Finally, we report the results of our investigation into the impact of these factors in combination.

    DOI: 10.58346/jisis.2024.i3.018

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  • Exploring the Discovery Process of Fresh IPv6 Prefixes: An Analysis of Scanning Behavior in Darknet and Honeynet Reviewed

    Liang Zhao, Satoru Kobayashi, Kensuke Fukuda

    Passive and Active Measurement Conference (PAM 2024), Lecture Notes in Computer Science (LNCS)   14537   95 - 111   2024.3

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    Language:English   Publishing type:Research paper (international conference proceedings)   Publisher:Springer Nature Switzerland  

    DOI: 10.1007/978-3-031-56249-5_4

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  • netroub: Towards an Emulation Platform for Network Trouble Scenarios Reviewed International coauthorship

    Colin Regal-Mezin, Satoru Kobayashi, Toshihiro Yamauchi

    Proceedings of the CoNEXT Student Workshop 2023   17 - 18   2023.12

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    Language:English   Publishing type:Research paper (international conference proceedings)   Publisher:ACM  

    DOI: 10.1145/3630202.3630222

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  • Analyzing Post-injection Attacker Activities in IoT Devices: A Comprehensive Log Analysis Approach Reviewed International coauthorship

    Hervet Victor, Satoru Kobayashi, Toshihiro Yamauchi

    Proceedings of the 2023 Eleventh International Symposium on Computing and Networking Workshops (CANDARW)   292 - 297   2023.11

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    Authorship:Corresponding author   Language:English   Publishing type:Research paper (international conference proceedings)  

    DOI: 10.1109/CANDARW60564.2023.00055

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  • Evaluation of Effectiveness of MAC Systems Based on LSM for Protecting IoT Devices Reviewed

    Masato Miki, Toshihiro Yamauchi, Satoru Kobayashi

    Proceedings of the 11th International Symposium on Computing and Networking (CANDAR 2023)   161 - 167   2023.11

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    Language:English   Publishing type:Research paper (international conference proceedings)  

    DOI: 10.1109/CANDAR60563.2023.00029

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  • dot2net: A labeled graph approach for template-based configuration of emulation networks Reviewed

    Satoru Kobayashi, Ryusei Shiiba, Ryosuke Miura, Shinsuke Miwa, Toshiyuki Miyachi, Kensuke Fukuda

    Proceedings of the 19th International Conference on Network and Service Management (CNSM 2023)   319 - 327   2023.11

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    Authorship:Lead author   Language:English   Publishing type:Research paper (international conference proceedings)  

    DOI: 10.23919/CNSM59352.2023.10327865

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  • An Implementation of Effective Server Resource Management Scheme Using Deep Reinforcement Learning Reviewed

    Toshiki Kawakita, Kimihiro Mizutani, Satoru Kobayashi, Kensuke Fukuda, Osamu Akashi

    Proceedings of the International Conference on Emerging Technologies for Communications   ( S8-5 )   1 - 1   2022.11

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    Language:Japanese   Publishing type:Research paper (international conference proceedings)  

    DOI: 10.34385/proc.72.S8-5

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  • A Novel Network Configuration Generation Scheme from Network Operator's Intent Described by Natural Language Reviewed

    Masaya Suzuki, Kimihiro Mizutani, Satoru Kobayashi, Kensuke Fukuda, Osamu Akashi

    Proceedings of the International Conference on Emerging Technologies for Communications   ( S2-1 )   1 - 1   2022.11

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    Language:Japanese   Publishing type:Research paper (international conference proceedings)  

    DOI: 10.34385/proc.72.S2-1

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  • Comparative Causal Analysis of Network Log Data in Two Large ISPs Reviewed

    Satoru Kobayashi, Keiichi Shima, Kenjiro Cho, Osamu Akashi, Kensuke Fukuda

    Proceedings of the 7th IEEE/IFIP International Workshop on Analytics for Network and Service Management (AnNet 2022)   2022.4

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    Authorship:Lead author   Language:English   Publishing type:Research paper (international conference proceedings)  

    DOI: 10.1109/NOMS54207.2022.9789823

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  • amulog: A general log analysis framework for comparison and combination of diverse template generation methods Reviewed International journal

    Satoru Kobayashi, Yuya Yamashiro, Kazuki Otomo, Kensuke Fukuda

    International Journal of Network Management   32 ( 4 )   2021.12

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    Authorship:Lead author   Language:English   Publishing type:Research paper (scientific journal)   Publisher:Wiley  

    DOI: 10.1002/nem.2195

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    Other Link: https://onlinelibrary.wiley.com/doi/full-xml/10.1002/nem.2195

  • A Scheme of Extracting Network Configuration Template Blocks Based on Tucker Decomposition Reviewed

    Daisuke Hanamitsu, Kimihiro Mizutani, Satoru Kobayashi, Kensuke Fukuda, Osamu Akashi

    Proceedings of the International Conference on Emerging Technologies for Communications   ( P1-14 )   1 - 1   2021.12

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    Language:Japanese   Publishing type:Research paper (international conference proceedings)  

    DOI: 10.34385/proc.68.P1-14

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  • Verifying Network Properties in SRv6 based Service Function Chaining Reviewed

    Ryusei Shiiba, Satoru Kobayashi, Osamu Akashi, Kensuke Fukuda

    Proceesings of the 16th Asian Internet Engineering Conference (AINTEC 2021)   18 - 26   2021.12

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    Language:English   Publishing type:Research paper (international conference proceedings)  

    DOI: 10.1145/3497777.3498546

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    Other Link: https://dblp.uni-trier.de/db/conf/aintec/aintec2021.html#ShiibaKAF21

  • Towards Extracting Semantics of Network Config Blocks Reviewed

    Kazuki Otomo, Satoru Kobayashi, Kensuke Fukuda, Osamu Akashi, Kimihiro Mizutani, Hiroshi Esaki

    Proceesings of the 9th IEEE International Workshop on Architecture, Design, Deployment & Management of Networks & Applications (ADMNET 2021)   1438 - 1443   2021.7

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    Language:English   Publishing type:Research paper (international conference proceedings)   Publisher:IEEE  

    DOI: 10.1109/COMPSAC51774.2021.00214

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    Other Link: https://dblp.uni-trier.de/db/conf/compsac/compsac2021.html#OtomoKFAME21

  • A Quantitative Causal Analysis for Network Log Data Reviewed International coauthorship

    Richard Jarry, Satoru Kobayashi, Kensuke Fukuda

    Proceedings of the 9th IEEE International Workshop on Architecture, Design, Deployment & Management of Networks & Applications (ADMNET 2021)   1444 - 1449   2021.7

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    Authorship:Corresponding author   Language:English   Publishing type:Research paper (international conference proceedings)  

    DOI: 10.1109/COMPSAC51774.2021.00213

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  • LogDTL: Network Log Template Generation with Deep Transfer Learning Reviewed International coauthorship

    Thieu Nguyen, Satoru Kobayashi, Kensuke Fukuda

    Proceedings of the 6th IEEE/IFIP International Workshop on Analytics for Network and Service Management (AnNet 2021)   848 - 853   2021.5

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  • Latent Semantics Approach for Network Log Analysis: Modeling and its application Reviewed

    Kazuki Otomo, Satoru Kobayashi, Kensuke Fukuda, Hiroshi Esaki

    Proceedings of the 17th IFIP/IEEE International Symposium on Integrated Network Management (IM 2021)   215 - 223   2021.5

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  • amulog: A General Log Analysis Framework for Diverse Template Generation Methods Reviewed

    Satoru Kobayashi, Yuya Yamashiro, Kazuki Otomo, Kensuke Fukuda

    Proceedings of the CNSM 2020   2020.11

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    Authorship:Lead author   Language:English   Publishing type:Research paper (international conference proceedings)  

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  • 大規模 IPv6 アドレスの収集・分析 Reviewed

    新津雄大, 小林諭, 福田健介, 江崎浩

    電子情報通信学会論文誌   J103-B ( 6 )   223 - 233   2020.6

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    Language:Japanese   Publishing type:Research paper (scientific journal)  

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  • Causal analysis of network logs with layered protocols and topology knowledge Reviewed

    Satoru Kobayashi, Kazuki Otomo, Kensuke Fukuda

    Proceedings of CNSM 2019   2019.10

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    Authorship:Lead author   Language:English   Publishing type:Research paper (international conference proceedings)  

    DOI: 10.23919/CNSM46954.2019.9012718

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  • Latent Variable based Anomaly Detection in Network System Logs Reviewed

    Kazuki Otomo, Satoru Kobayashi, Kensuke Fukuda, Hiroshi Esaki

    IEICE Transactions on Information and Systems   E102-D ( 9 )   1644 - 1652   2019.9

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    Language:English   Publishing type:Research paper (scientific journal)  

    DOI: 10.1587/transinf.2018OFP0007

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  • ARP Request Trend Fitting for Detecting Malicious Activity in LAN Reviewed

    Kai Matsufuji, Satoru Kobayashi, Hiroshi Esaki, Hideya Ochiai

    Proceedings of IMCOM 2019   89 - 96   2019.1

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    Language:English   Publishing type:Research paper (international conference proceedings)  

    DOI: 10.1007/978-3-030-19063-7_8

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  • Finding Anomalies in Network System Logs with Latent Variables Reviewed

    Kazuki Otomo, Satoru Kobayashi, Kensuke Fukuda, Hiroshi Esaki

    Workshop on Big Data Analytics and Machine Learning for Data Communication Networks (BigDAMA)   8 - 14   2018.8

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    Language:English   Publishing type:Research paper (international conference proceedings)  

    DOI: 10.1145/3229607.3229608

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  • Mining Causality of Network Events in Log Data Reviewed

    Satoru Kobayashi, Kazuki Otomo, Kensuke Fukuda, Hiroshi Esaki

    IEEE Transactions on Network and Service Management   15 ( 1 )   53 - 67   2018.3

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    Authorship:Lead author   Language:English   Publishing type:Research paper (scientific journal)   Publisher:Institute of Electrical and Electronics Engineers Inc.  

    Network log messages (e.g., syslog) are expected to be valuable and useful information to detect unexpected or anomalous behavior in large scale networks. However, because of the huge amount of system log data collected in daily operation, it is not easy to extract pinpoint system failures or to identify their causes. In this paper, we propose a method for extracting the pinpoint failures and identifying their causes from network syslog data. The methodology proposed in this paper relies on causal inference that reconstructs causality of network events from a set of time series of events. Causal inference can filter out accidentally correlated events, thus it outputs more plausible causal events than traditional cross-correlation-based approaches can. We apply our method to 15 months' worth of network syslog data obtained from a nationwide academic network in Japan. The proposed method significantly reduces the number of pseudo correlated events compared with the traditional methods. Also, through three case studies and comparison with trouble ticket data, we demonstrate the effectiveness of the proposed method for practical network operation.

    DOI: 10.1109/TNSM.2017.2778096

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  • Analyzing Burstness and Casuality of System logs Reviewed

    Kazuki Otomo, Satoru Kobayashi, Kensuke Fukuda, Hiroshi Esaki

    ACM SIGCOMM CoNEXT 2017 Student Workshop   2017.12

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    Language:English   Publishing type:Research paper (international conference proceedings)  

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  • An Analysis of Burstiness and Causality of System Logs Reviewed

    Kazuki Otomo, Satoru Kobayashi, Kensuke Fukuda, Hiroshi Esaki

    Proceedings of AINTEC 2017   2017.11

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  • Mining causes of network events in log data with causal inference Reviewed

    Satoru Kobayashi, Kensuke Fukuda, Hiroshi Esaki

    Proceedings of the IM 2017 - 2017 IFIP/IEEE International Symposium on Integrated Network and Service Management   45 - 53   2017.7

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    Authorship:Lead author   Language:English   Publishing type:Research paper (international conference proceedings)   Publisher:Institute of Electrical and Electronics Engineers Inc.  

    Network log message (e.g., syslog) is valuable information to detect unexpected or anomalous behavior in a large scale network. However, pinpointing failures and their causes is not an easy problem because of a huge amount of system log data in daily operation. In this study, we propose a method extracting failures and their causes from network syslog data. The main idea of the method relies on causal inference that reconstructs causality of network events from a set of the time series of events. Causal inference allows us to reduce the number of correlated events by chance, thus it outputs more plausible causal events than a traditional cross-correlation based approach. We apply our method to 15 months network syslog data obtained in a nation-wide academic network in Japan. Our method significantly reduces the number of pseudo correlated events compared with the traditional method. Also, through two case studies and comparison with trouble ticket data, we demonstrate the effectiveness of our method for network operation.

    DOI: 10.23919/INM.2017.7987263

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  • Application of Change Point Detection to System Logs for Fault Detection Reviewed

    Yu Komohara, Satoru Kobayashi, Hideya Ochiai, Hiroshi Esaki

    ACM SIGCOMM CoNEXT 2016 Student Workshop (Poster Session)   2016.12

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    Language:English   Publishing type:Research paper (international conference proceedings)  

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  • Causation mining in network logs Reviewed

    Satoru Kobayashi, Kensuke Fukuda, Hiroshi Esaki

    ACM SIGCOMM CoNEXT 2016 Student Workshop   2016.12

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    Authorship:Lead author   Language:English   Publishing type:Research paper (international conference proceedings)  

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  • Towards an NLP-based log template generation algorithm for system log analysis Reviewed

    Satoru Kobayashi, Kensuke Fukuda, Hiroshi Esaki

    Proceedings of CFI 2014   2014.6

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    Authorship:Lead author   Language:English   Publishing type:Research paper (international conference proceedings)  

    DOI: 10.1145/2619287.2619290

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MISC

  • 偽ショッピングサイトへ誘導する踏み台サイトの検出のための実態調査

    道下大悟, 小林 諭, 山内利宏

    コンピュータセキュリティシンポジウム 2024 (CSS2024) 論文集   1095 - 1101   2024.10

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    Language:Japanese   Publishing type:Research paper, summary (national, other academic conference)  

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  • 実行ファイルにおける関数配置順序ランダム化手法の適用によるコード再利用攻撃への耐性評価

    佐治和馬, 山内利宏, 小林 諭, 谷口秀夫

    コンピュータセキュリティシンポジウム 2024 (CSS2024) 論文集   8 - 15   2024.10

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  • シグナル受信処理の即時実行開始手法

    大野 裕美子, 山内 利宏, 小林 諭, 谷口 秀夫

    情報処理学会第86回全国大会講演論文集   2024.3

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  • ネットワークログの対話的因果解析の検討

    小林諭, 石井 宏典, 山内 利宏, 明石 修, 福田 健介

    電子情報通信学会技術研究報告 : 信学技報   123 ( 422 )   233 - 240   2024.3

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    Authorship:Lead author   Language:Japanese   Publishing type:Research paper, summary (national, other academic conference)  

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  • ネットワークログ解析におけるイベント間因果情報可視化の検討

    石井宏典, 小林諭, 福田健介, 山内利宏

    電子情報通信学会総合大会   B-7-25   2024.3

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  • HPCにおけるGang Schedulingの切替間隔動的変更手法

    西本 伊織, 山内 利宏, 小林 諭, 加藤 純, 三輪 真弘, 谷口 秀夫

    情報処理学会研究報告   2024-OS-162 ( 15 )   1 - 7   2024.2

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  • 実行ファイルにおける関数配置順序のランダム化によるコード再利用攻撃への耐性向上手法の提案

    佐治和馬, 山内利宏, 小林諭, 谷口秀夫

    情報処理学会シンポジウムシリーズ コンピュータセキュリティシンポジウム 2023 (CSS2023) 論文集   2023   1357 - 1364   2023.10

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  • Implementation of Function for Tracing Diffusion of Classified Information to Support Inter-VM Communication on KVM

    Kohei Otani, Satoru Kobayashi, Toshihiro Yamauchi, Hideo Taniguchi

    IPSJ SIG Technical Report   2023-CSEC-100 ( 62 )   1 - 8   2023.3

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  • HPCクラウドにおける割り込み処理によるOSノイズの影響の評価

    西本伊織, 小林諭, 山内利宏, 加藤純, 佐藤充, 谷口秀夫

    情報処理学会研究報告   2023-OS-158 ( 28 )   1 - 7   2023.2

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  • ネットワークコンフィグの潜在的特徴抽出手法の提案と評価

    花光 大輔, 水谷 后宏, 小林 諭, 福田 健介, 明石 修

    2022年度 情報処理学会関西支部 支部大会 講演論文集   ( G-02 )   2022.9

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  • Towards a Collaborative Operational Data Analysis for Automated Network Management

    Satoru Kobayashi, Kensuke Fukuda

    IEICE Technical Report   122 ( 85 )   1 - 7   2022.6

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    Authorship:Lead author   Language:Japanese   Publishing type:Internal/External technical report, pre-print, etc.  

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  • Automatic Document Labelling to Network Log Data

    Ayato Tokubi, Kazuki Otomo, Satoru Kobayashi, Kensuke Fukuda, Hiroshi Esaki

    IEICE Technical Report   120 ( 186 )   1 - 6   2020.10

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  • Design of Honeynet to avoid IPv6 alias detection

    Hyuga Kobayashi, Satoru Kobayashi, Kensuke Fukuda, Hiroshi Esaki

    IEICE Technical Report   119 ( 343 )   13 - 18   2019.12

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  • Improving Network Log Analysis by Semantics

    Kazuki Otomo, Satoru Kobayashi, Kensuke Fukuda, Hiroshi Esaki

    IEICE Technical Report   119 ( 343 )   7 - 12   2019.12

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  • Log Template Estimation with Bridged Refinement

    Yuya Yamashiro, Satoru Kobayashi, Kensuke Fukuda, Hiroshi Esaki

    IEICE Technical Report   119 ( 318 )   13 - 18   2019.11

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  • Towards application of network topology information to network log causal anlaysis

    Satoru Kobayashi, Kazuki Otomo, Kensuke Fukuda

    IEICE Technical Report   118 ( 360 )   1 - 8   2018.12

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    Authorship:Lead author   Language:Japanese   Publishing type:Internal/External technical report, pre-print, etc.  

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  • Collecting a large number of active IPv6 addresses

    Yudai Aratsu, Satoru Kobayashi, Kensuke Fukuda, Hiroshi Esaki

    IEICE Technical Report   118 ( 204 )   1 - 8   2018.9

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  • Network Log Template Generation from Open Source Software

    Yuya Yamashiro, Satoru Kobayashi, Kensuke Fukuda, Hiroshi Esaki

    IEICE Technical Report   118 ( 204 )   15 - 22   2018.9

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Presentations

  • Design and Implementation of IPv6 Scan Detection System

    Liang Zhao, Satoru Kobayashi, Kensuke Fukuda

    IEICE General Conference  2023.3.10 

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    Event date: 2023.3.7 - 2023.3.10

    Language:English   Presentation type:Poster presentation  

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  • Toward a compositional data plane verification for large-scale networks

    Ryusei Shiiba, Satoru Kobayashi, Osamu Akashi, Kensuke Fukuda

    The 17th Asian Internet Engineering Conference (AINTEC 2022)  2022.12.20 

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    Event date: 2022.12.19 - 2022.12.21

    Language:Japanese   Presentation type:Poster presentation  

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  • Causal Analysis of Network Log Events Invited

    Satoru Kobayashi

    JFLI Workshop 2020 on Next Generation Networking  2020.2.18 

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    Event date: 2020.2.17 - 2020.2.18

    Language:English   Presentation type:Oral presentation (invited, special)  

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  • Dot2tinet: A graph-based network configuration platform for large-scale emulation networks

    Satoru Kobayashi, Ryusei Shiiba, Kensuke Fukuda

    The 17th Asian Internet Engineering Conference (AINTEC 2022)  2022.12.20 

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  • Approach to Better Log Template Generation

    Yuya Yamashiro, Satoru Kobayashi, Kensuke Fukuda, Hiroshi Esaki

    Internet Conference 2018  2018.11 

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    Language:English   Presentation type:Poster presentation  

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  • Collecting a large number of active IPv6 addresses

    Yudai Aratsu, Satoru Kobayashi, Kensuke Fukuda, Hiroshi Esaki

    Internet Conference 2018  2018.11 

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  • Mining causality of network events in log data Invited

    Satoru Kobayashi

    International Cloud Resiliency Workshop  2018.10.17 

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Awards

  • CSS2023奨励賞

    2023.11   コンピュータセキュリティシンポジウム2023   実行ファイルにおける関数配置順序のランダム化によるコード再利用攻撃への耐性向上手法の提案

    佐治和馬, 山内利宏, 小林諭, 谷口秀夫

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  • IA研究賞(優秀研究賞)

    2021.6   電子情報通信学会 インターネットアーキテクチャ研究会   ネットワークログデータへの自動文書ラベリングの提案

    徳備彩人, 大友 一樹, 小林 諭, 福田 健介, 江崎 浩

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  • IA研究賞(優秀研究賞)

    2019.6   電子情報通信学会 インターネットアーキテクチャ研究会   大規模IPv6アドレス収集手法に関する検討

    新津 雄大, 小林 諭, 福田 健介, 江崎 浩

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    Award type:Award from Japanese society, conference, symposium, etc. 

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  • Dean’s award for outstanding thesis (master’s thesis)

    2015.3   The University of Tokyo, Graduate school of Information Science and Technology  

    Satoru Kobayashi

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Research Projects

  • ネットワーク障害原因究明支援技術へのオペレータ知識導入に関する研究

    2024.04 - 2025.03

    国立情報学研究所  2024年度 国立情報学研究所公募型共同研究 戦略研究公募型 

    小林諭, 福田健介, 明石修

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    Authorship:Principal investigator 

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  • ネットワーク障害原因究明支援に向けたネットワークログ対話的因果解析のための運用データ統合可視化システムの研究

    Grant number:23S0901  2023.04 - 2024.03

    国立情報学研究所  2023年度 国立情報学研究所公募型共同研究 戦略研究公募型 

    小林諭, 福田健介, 山内利宏, 明石修

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  • 機器毎のソフトウェア構成変更による攻撃難化と攻撃耐性を持つ基盤ソフトウェアの研究

    Grant number:22H03592  2022.04 - 2026.03

    日本学術振興会  科学研究費助成事業  基盤研究(B)

    山内 利宏, 谷口 秀夫, 森山 英明, 佐藤 将也, 葛野 弘樹, 小林 諭

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    Authorship:Coinvestigator(s)  Grant type:Competitive

    Grant amount:\17290000 ( Direct expense: \13300000 、 Indirect expense:\3990000 )

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  • 機器毎のソフトウェア構成変更による攻撃難化と攻撃耐性を持つ基盤ソフトウェアの研究

    Grant number:23K24848  2022.04 - 2026.03

    日本学術振興会  科学研究費助成事業  基盤研究(B)

    山内 利宏, 谷口 秀夫, 森山 英明, 佐藤 将也, 葛野 弘樹, 小林 諭

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    Grant amount:\17290000 ( Direct expense: \13300000 、 Indirect expense:\3990000 )

    本年度は,研究計画に基づき,3つの課題について以下の研究を行った.
    (研究1)機器毎のOSやAPのカスタム化による攻撃難化手法の研究については,実行ファイルのオブジェクトファイルをリンクする順番を変更することにより,ROPなどの攻撃を困難にする手法を検討し,基本方式を実現した.この手法により,攻撃困難化が可能な攻撃について検討した.また,オープンソースソフトウェアにおけるセキュリティリスクの評価手法について検討した.
    (研究2)VMMによる機密情報拡散追跡と監査支援の研究については,同一VMM上のVM間の機密情報の拡散追跡と制御について検討した.同一VMM上のVM間での情報を伝搬させる処理について検討し,ソケット通信とNFSで利用するRPCに着目して,機密情報の伝搬を把握する手法を検討し,基本方式を実現した.また,複数のVMを対象とした機密情報の追跡機能において,マルチコアCPUの複数コアを用いて追跡処理を実現する手法を提案し,有効性を示した.さらに,VMMからVMのシステムコールをフックする箇所を自動的に推定する手法を提案し,有効性を示した.
    (研究3)OSの仮想記憶空間の隔離による攻撃耐性の向上手法の研究については,Linuxカーネルの脆弱性を悪用するPoC(Proof of Concept)コードの実行により,実行されるカーネル関数をトレースにより明らかにする手法を検討し,実現した.この機能により,カーネルの脆弱性を緩和するために,どのような処理を制限すれば良いのかを把握することができる.また,Linuxカーネル用の仮想記憶空間を複数用意し,カーネルの脆弱性を悪用するコードの実行により,重要なカーネルデータや保護機能のコードが改ざんされるのを防止する機構を検討し,有効性を示した.また,Linuxカーネルのメモリをページ単位でアクセス制御する手法を提案し,攻撃コードによる改ざんを防止できることを示した.

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  • ネットワーク自動運用のための運用データ連携解析

    Grant number:22K17886  2022.04 - 2025.03

    日本学術振興会  科学研究費助成事業  若手研究

    小林 諭

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    Authorship:Principal investigator 

    Grant amount:\4680000 ( Direct expense: \3600000 、 Indirect expense:\1080000 )

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  • セマンティクス抽出と因果解析によるネットワーク障害対応支援に関する研究

    2019.06 - 2022.03

    総務省  戦略的情報通信研究開発推進制度 

    福田健介, 小林諭, 明石修, 長健二朗, 島慶一

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    Authorship:Coinvestigator(s)  Grant type:Competitive

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  • Knowledge mining of large-scale network operational data for troubleshooting and predictive analysis

    Grant number:19K20262  2019.04 - 2021.03

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research  Grant-in-Aid for Early-Career Scientists

    Kobayashi Satoru

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    Authorship:Principal investigator  Grant type:Competitive

    In this research, we proposed a new analysis approach for network operational data on the basis of causal inference, to help troubleshooting of large-scale networks. We proposed two analysis frameworks: "amulog", a general log analysis framework to estimate log templates and classify messages with them in online processing, and "logdag", a causal analysis framework designed for network operational data including logs and measured SNMP data. The proposed technology will help operators to extract contextual information in operational data automatically.

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