Satoru Kobayashi

Profile

Publications

Journal

  1. 新津 雄大, 小林 諭, 福田 健介, 江崎 浩, “大規模IPv6アドレスの収集・分析”, 電子情報通信学会論文誌, Vol.J103-B, No.6, pp.223-233, Jun, 2020 (10.14923/transcomj.2019JBT0002)

  2. Kazuki Otomo, Satoru Kobayashi, Kensuke Fukuda, Hiroshi Esaki, “Latent Variable based Anomaly Detection in Network System Logs”, IEICE Transactions on Information and Systems, pp.1644-1652, Vol.E102-D, No.9, September, 2019 (10.1587/transinf.2018OFP0007)

  3. Satoru Kobayashi, Kazuki Otomo, Kensuke Fukuda, Hiroshi Esaki, “Mining Causality of Network Events in Log Data”, IEEE Transactions on Network and Service Management, pp.53-67, vol.15, no.1, March, 2018 (10.1109/TNSM.2017.2778096, paper)

International Conference (w/ review)

  1. Kazuki Otomo, Satoru Kobayashi, Kensuke Fukuda, Osamu Akashi, Kimihiro Mizutani, Hiroshi Esaki, “Towards Extracting Semantics of Network Config Blocks”, the 9th IEEE International Workshop on Architecture, Design, Deployment & Management of Networks & Applications (ADMNET 2021), pp.1444-1449, Virtual, July, 2021 (10.1109/COMPSAC51774.2021.00214)

  2. Richard Jarry, Satoru Kobayashi, Kensuke Fukuda, “A Quantitative Causal Analysis for Network Log Data”, the 9th IEEE International Workshop on Architecture, Design, Deployment & Management of Networks & Applications (ADMNET 2021), pp.1438-1443, Virtual, July, 2021 (10.1109/COMPSAC51774.2021.00213, slide)

  3. Thieu Nguyen, Satoru Kobayashi, Kensuke Fukuda, “LogDTL: Network Log Template Generation with Deep Transfer Learning”, the 6th IEEE/IFIP International Workshop on Analytics for Network and Service Management (AnNet 2021), pp.848-853, Virtual, May, 2021 (IFIP, IEEE, slide)

  4. Kazuki Otomo, Satoru Kobayashi, Kensuke Fukuda, Hiroshi Esaki, “Latent Semantics Approach for Network Log Analysis: Modeling and its application”, the 17th IFIP/IEEE International Symposium on Integrated Network Management (IM’21), pp.215-223, Virtual, May, 2021 (IFIP, IEEE)

  5. Satoru Kobayashi, Yuya Yamashiro, Kazuki Otomo, Kensuke Fukuda, “amulog: A General Log Analysis Framework for Diverse Template Generation Methods”, the 16th IFIP/IEEE International Conference on Network and Service Management (CNSM’20), pp.1-5, Virtual, November, 2020 (10.23919/CNSM50824.2020.9269049, IFIP, paper, poster, slide)

  6. Satoru Kobayashi, Kazuki Otomo, Kensuke Fukuda, “Causal analysis of network logs with layered protocols and topology knowledge”, the 15th IFIP/IEEE International Conference on Network and Service Management (CNSM’19), pp.1-9, Halifax, Canada, October, 2019 (10.23919/CNSM46954.2019.9012718, IFIP, paper, slide)

  7. Kai Matsufuji, Satoru Kobayashi, Hiroshi Esaki, Hideya Ochiai, “ARP Request Trend Fitting for Detecting Malicious Activity in LAN”, International Conference on Ubiquitous Information Management and Communication (IMCOM), pp.89-96, Phuket, Thailand, January, 2019 (10.1007/978-3-030-19063-7_8)

  8. Kazuki Otomo, Satoru Kobayashi, Kensuke Fukuda, Hiroshi Esaki, “Finding Anomalies in Network System Logs with Latent Variables”, Workshop on Big Data Analytics and Machine Learning for Data Communication Networks (Big-DAMA), ACM SIGCOMM, pp.8-14, Budapest, Hungary, August, 2018 (10.1145/3229607.3229608)

  9. Kazuki Otomo, Satoru Kobayashi, Kensuke Fukuda, Hiroshi Esaki, “Analyzing Burstiness and Causality of System logs”, the 13th International Conference on emerging Networking EXperiments and Technologies (CoNEXT’17) Student Workshop, ACM SIGCOMM, p.2, Seoul, South Korea, December, 2017

  10. Kazuki Otomo, Satoru Kobayashi, Kensuke Fukuda, Hiroshi Esaki, “An Analysis of Burstiness and Causality of System Logs”, Asian Internet Engineering Conference (AINTEC’17), pp.16-23, Bangkok, Thailand, November, 2017 (10.1145/3154970.3154973)

  11. Satoru Kobayashi, Kensuke Fukuda and Hiroshi Esaki, “Mining causes of network events in log data with causal inference”, the 13th IFIP/IEEE International Symposium on Integrated Network Management (IM’17), pp.45-53, Lisbon, Portugal, May, 2017 (10.23919/INM.2017.7987263, IFIP paper, slide)

  12. Satoru Kobayashi, Kensuke Fukuda and Hiroshi Esaki, “Causation mining in network logs”, the 12th International Conference on emerging Networking EXperiments and Technologies (CoNEXT’16) Student Workshop, ACM SIGCOMM, p.2, Irvine, California, December, 2016 (paper)

  13. Yu Komohara, Satoru Kobayashi, Hideya Ochiai, Hiroshi Esaki, “Application of Change Point Detection to System Logs for Fault Detection”, the 12th International Conference on emerging Networking EXperiments and Technologies (CoNEXT’16) Student Workshop (Poster Session), p.2, Irvine, California, December, 2016

  14. Satoru Kobayashi, Kensuke Fukuda, Hiroshi Esaki, “Towards an NLP-based Log Template Generation Algorithm for System Log Analysis”, the Ninth International Conference on Future Internet Technologies (CFI’14), p.4, Tokyo, Japan, June, 2014 (10.1145/2619287.2619290, paper)

Domestic Conference (w/ review)

  1. 大友 一樹, 小林 諭, 福田 健介, 江崎 浩, “システムログ異常予測に向けたバースト性と因果関係の解析”, The Eighteenth Workshop on Internet Technology (WIT2017), p.8, 愛媛, 2017年6月

Domestic Conference (w/o review)

  1. 小林 諭, 江崎 浩, “CLI環境におけるオペレーションミス低減手法の検討と実装”, 電子情報通信学会総合大会, p.1, 岐阜, 2013年3月

Technical Report

  1. 徳備彩人, 大友 一樹, 小林 諭, 福田 健介, 江崎 浩, “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”, 信学技報, vol. 120, no. 186, IA2020-14, pp. 1-6, 2020年10月 (2020年度IA研究賞(優秀賞), link)

  2. 大友 一樹, 小林 諭, 福田 健介, 江崎 浩, “ネットワークログ解析におけるセマンティクス活用の検討”, 信学技報, vol. 119, no. 343, IA2019-49, pp. 7-12, 2019年12月 (link)

  3. 小林 日向, 新津 雄大, 小林 諭, 福田 健介, 江崎 浩, “IPv6エイリアス空間検出を考慮したハニーネットの検討”, 信学技報, vol. 119, no. 343, IA2019-50, pp. 13-18, 2019年12月 (link)

  4. 山城 裕陽, 小林 諭, 福田 健介, 江崎 浩, “Bridged Refinementによるログテンプレート推定手法の検討”, 信学技報, vol. 119, no. 318, IA2019-45, pp. 13-18, 2019年11月 (link)

  5. 小林 諭, 大友 一樹, 福田 健介, “ネットワーク構成情報を考慮したネットワークログ因果解析の検討”, 信学技報, vol. 118, no. 360, IA2018-40, pp. 1-8, 2018年12月 (link)

  6. 山城 裕陽, 小林 諭, 福田 健介, 江崎 浩, “ソースコードからのネットワークログテンプレート自動生成に関する検討”, 信学技報, vol. 118, no. 204, IA2018-18, pp. 15-22, 2018年9月 (link)

  7. 新津 雄大, 小林 諭, 福田 健介, 江崎 浩, “大規模IPv6アドレス収集手法の検討”, 信学技報, vol. 118, no. 204, IA2018-16, pp. 1-8, 2018年9月 (2018年度IA研究賞(優秀賞)) (link)

Ph.D. Thesis

Activities

Oral Presentation

  1. Satoru Kobayashi, “Causal Analysis of Network Log Events”, JFLI Workshop 2020 on Next Generation Networking, Tokyo, Japan, Feb, 2020 (Invited, link, slide)

  2. Satoru Kobayashi, “Mining causality of network events in log data”, International Cloud Resiliency Workshop 2018, Xi’an, China, Oct, 2018 (Invited, link, slide)

Poster Presentation

  1. Yuya Yamashiro, Satoru Kobayashi, Kensuke Fukuda, Hiroshi Esaki, “Approach to Better Log Template Generation”, Internet Conference 2018, Tokyo, Japan, Nov, 2018 (Poster Award)

  2. Yudai Aratsu, Satoru Kobayashi, Kensuke Fukuda, Hiroshi Esaki, “Collecting a large number of active IPv6 addresses”, Internet Conference 2018, Tokyo, Japan, Nov, 2018 (Poster Award)

  3. 小林 諭, 福田 健介, 江崎 浩, “システムログの意味抽出のための自然言語処理的アプローチによる解析手法の検討”, インターネットコンファレンス2013, p.2, 東京, 2013年10月

Awards

  1. 徳備彩人, 大友 一樹, 小林 諭, 福田 健介, 江崎 浩, 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IA研究賞(優秀研究賞) “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”, Jun, 2021

  2. 新津 雄大, 小林 諭, 福田 健介, 江崎 浩, 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IA研究賞(優秀研究賞) “大規模IPv6アドレス収集手法に関する検討”, Jun, 2019

  3. IEEE/IFIP IM 2017 Student Travel Grants, May, 2017

  4. ACM SIGCOMM Grants/CoNext 2016, Dec, 2016

  5. Dean’s award for outstanding thesis (master’s thesis), March, 2015

Research Funds

  1. 科研費若手研究, “トラブルシューティング・予測のための大規模ネットワークシステムログからの知識抽出”, 2019年度-2020年度 (19K20262, 研究代表者)

  2. 戦略的情報通信研究開発推進事業(SCOPE)社会展開指向型研究開発(3年枠), “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年度-2021年度 (研究分担者)

Committee

  1. IPSJ Journal Reviewer, 2021-Current

External Peer Review

  1. IEEE Transactions on Network and Service Management, 2019-2020

  2. IEICE Transactions on Communications, 2018

  3. IEEE International Workshop on Big Data Management and Infrastructure for the Internet of Things, 2018

Lecture

Others

Satoru Kobayashi received the Ph.D. degree in information science and technology from the University of Tokyo, Tokyo Japan, in 2018.
He is a Project Researcher at the National Institute of Informatics (NII).
His research interests are network management and data mining.

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