The method of detecting malware-infected hosts analyzing firewall and proxy logs. - Kazunori Kamiya; Kazufumi Aoki; Kensuke Nakata; Toru Sato; Hiroshi Kurakami; Masaki Tanikawa (APSITT, 2015)

Alchemy: Stochastic Feature Regeneration for Malicious Network Traffic Classification. - Bo Hu; Atsutoshi Kumagai; Kazunori Kamiya; Kenji Takahashi; Daniel Dalek; Ola Söderström; Kazuya Okada; Yuji Sekiya; Akihiro Nakao (COMPSAC (1), 2019)

Subspace Clustering for Interpretable Botnet Traffic Analysis. - Shohei Araki; Kneji Takahashi; Bo Hu; Kazunori Kamiya; Masaki Tanikawa (ICC, 2019)

Piper: A Unified Machine Learning Pipeline for Internet-scale Traffic Analysis. - Bo Hu; Kazunori Kamiya; Kenji Takahashi; Akihiro Nakao (GLOBECOM, 2020)

SILU: Strategy Involving Large-scale Unlabeled Logs for Improving Malware Detector. - Taishi Nishiyama; Atsutoshi Kumagai; Kazunori Kamiya; Kenji Takahashi (ISCC, 2020)

Large-Scale Network-Traffic-Identification Method with Domain Adaptation. - Shun Tobiyama; Bo Hu; Kazunori Kamiya; Kenji Takahashi (WWW (Companion Volume), 2020)

Sharpshooting Most Beneficial Part of AUC for Detecting Malicious Logs. - Taishi Nishiyama; Atsutoshi Kumagai; Akinori Fujino; Kazunori Kamiya (AusDM, 2021)

Multi-hop Graph Embedding for Botnet Detection. - Bo Hu; Kazunori Kamiya; Kenji Takahashi; Akihiro Nakao (GLOBECOM, 2021)

SamE: Sampling-based Embedding for Learning Representations of the Internet. - Bo Hu; Kazunori Kamiya; Kenji Takahashi; Akihiro Nakao (GLOBECOM, 2021)

Balanced Score Propagation for Botnet Detection. - Shosuke Oba; Bo Hu; Kazunori Kamiya; Kenji Takahashi (ICC, 2022)

Malicious Log Detection Using Machine Learning to Maximize the Partial AUC. - Taishi Nishiyama; Atsutoshi Kumagai; Akinori Fujino; Kazunori Kamiya (CCNC, 2024)

Partial AUC Maximization for Security Log Analysis Robust to Overfitting and Noisy Labels. - Taishi Nishiyama; Atsutoshi Kumagai; Akinori Fujino; Kazunori Kamiya (GLOBECOM, 2024)