Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
NS |
2023-04-14 11:40 |
Fukushima |
Nihon University, Koriyama Campus + Online (Primary: On-site, Secondary: Online) |
Network Anomaly Detection through Variable Granularity Traffic Analysis Shohei Kamamura, Yuya Takeda (Seikei Univ.), Yuki Takei, Masato Nishiguchi, Yuhei Hayashi, Takayuki Fujiwara (NTT) NS2023-9 |
In the Society 5.0, it is important to accurately measure and analyze the communication traffic flow in wide-area IP net... [more] |
NS2023-9 pp.44-49 |
CCS |
2023-03-26 10:35 |
Hokkaido |
RUSUTSU RESORT |
Acquisition of physical kinetics of machines by reservoir computing Sena Kojima, Koki Minagawa, Taisei Saito, Tetsuya Asai (Hokkaido Univ.) CCS2022-67 |
This report focuses on an anomaly detection application of a machine’s dynamical system using reservoir computing. We pr... [more] |
CCS2022-67 pp.25-30 |
IMQ, IE, MVE, CQ (Joint) [detail] |
2023-03-15 11:00 |
Okinawa |
Okinawaken Seinenkaikan (Naha-shi) (Primary: On-site, Secondary: Online) |
Evaluating the Efficiency of Anomaly Detection Methods for Temporal Networks Using the Graph Spectrum Masataka Nagao, Eriko Segawa, Yusuke Sakumoto (Kwansei Gakuin Univ.) CQ2022-83 |
LAD (Laplacian Anomaly Detection) is a method for detecting anomalies in dynamic networks using the eigenvalues (the gra... [more] |
CQ2022-83 pp.19-24 |
RCC, ISEC, IT, WBS |
2023-03-15 09:30 |
Yamaguchi |
(Primary: On-site, Secondary: Online) |
Networks anomaly detection by VAE based on features extracted by CNN Higashihata Kazuki (Osaka Prefecture Univ.), Aoki Shigeki, Miyamoto Takao (Osaka Metropolitan Univ.) IT2022-111 ISEC2022-90 WBS2022-108 RCC2022-108 |
Anomaly-based IDS, one of the intrusion detection systems (IDS), can detect unknown anomalies, but there is a problem of... [more] |
IT2022-111 ISEC2022-90 WBS2022-108 RCC2022-108 pp.269-276 |
R |
2023-03-10 13:50 |
Hiroshima |
(Primary: On-site, Secondary: Online) |
Failure Sign Detection by State Path Analysis for Fare Collection System
-- Evaluation by Sequential Pattern Mining with Mechatronics Knowledge -- Ken Ueno, Misato Ishikawa, Yuko Kobayashi, Takamitsu Sunaoshi (Toshiba), Kiyoku Endo (Toshiba Automation Systems Service) R2022-50 |
To detect failure sign on Fare Collection System (FCS) which has low failure rate accurately, we need the mechatronics k... [more] |
R2022-50 pp.13-18 |
MI |
2023-03-06 17:30 |
Okinawa |
OKINAWA SEINENKAIKAN (Primary: On-site, Secondary: Online) |
[Short Paper]
Novel loss function dedicated for anomaly detection using lesion-embedded artificial dataset
-- Normal/Abnormal Contrastive (NAC) loss -- Shouhei Hanaoka (Tokyo Univ.), Yukihiro Nomura (Chiba Univ.), Hisaichi Shibata, Tomomi Takenaga, Takeharu Yoshikawa, Naoto Hayashi, Osamu Abe (Tokyo Univ.) MI2022-98 |
(To be available after the conference date) [more] |
MI2022-98 pp.117-118 |
PRMU, IBISML, IPSJ-CVIM [detail] |
2023-03-02 10:35 |
Hokkaido |
Future University Hakodate (Primary: On-site, Secondary: Online) |
Investigation of Appearance Inspection Method Considering the Number of Corresponding Local Patches Katsuhisa Kitaguchi, Yohei Nishizaki, Mamoru Saito (ORIST) PRMU2022-74 IBISML2022-81 |
There has been a great deal of research on appearance inspection using deep learning, which learns only from normal imag... [more] |
PRMU2022-74 IBISML2022-81 pp.88-92 |
IN, NS (Joint) |
2023-03-02 16:50 |
Okinawa |
Okinawa Convention Centre + Online (Primary: On-site, Secondary: Online) |
A Dynamic Threshold Adjustment Method Between Arbitrary Nodes for Byte Consistency Check in SDN Jumpei Sato, Naoki Moriyama (TUMSAT), Takahiro Shimizu (LINE), Kohta Ohshima (TUMSAT), Naoya Kitagawa (NII) NS2022-214 |
(To be available after the conference date) [more] |
NS2022-214 pp.269-274 |
IN, NS (Joint) |
2023-03-03 11:00 |
Okinawa |
Okinawa Convention Centre + Online (Primary: On-site, Secondary: Online) |
Unidentified Floating Object Detecting Method in Maritime Environment using Efficient GAN Hiromu Habuka, Kohta Ohshima (TUMSAT) NS2022-230 |
(To be available after the conference date) [more] |
NS2022-230 pp.362-367 |
NS, ICM, CQ, NV (Joint) |
2022-11-24 14:15 |
Fukuoka |
Humanities and Social Sciences Center, Fukuoka Univ. + Online (Primary: On-site, Secondary: Online) |
Research on Anomaly Detection through Analysis of Observed Traffic Using Self-Attention Yuhang Zhou, Akihiro Nakao (UTokyo) NS2022-108 |
Nowadays, threat activities have become an integral part of our network lives. The sophistication and variety of differe... [more] |
NS2022-108 pp.47-52 |
NS, ICM, CQ, NV (Joint) |
2022-11-24 13:25 |
Fukuoka |
Humanities and Social Sciences Center, Fukuoka Univ. + Online (Primary: On-site, Secondary: Online) |
Anomaly Detection on Web Pages Using HDBSCAN and Deep SVDD Yusuke Noji, Tomotaka Kimura, Jun Cheng (Doshisha Univ.) CQ2022-51 |
In this paper, we propose an anomalous Web page detection method using Deep SVDD (Support Vector Data Description), whic... [more] |
CQ2022-51 pp.23-27 |
CAS, MSS, IPSJ-AL [detail] |
2022-11-18 14:25 |
Kochi |
(Primary: On-site, Secondary: Online) |
How to decide threshold value in anomaly detection using Wireless Ad hoc Federated Learning and Autoencoder Riku Nishihata, Hideya Ochial, Hiroshi Esaki (Univ. Tokyo) CAS2022-55 MSS2022-38 |
Machine learning requires a lot of data, but from the perspective of privacy and security, new learning methods without ... [more] |
CAS2022-55 MSS2022-38 pp.83-86 |
KBSE, SC |
2022-11-05 11:10 |
Nagano |
(Primary: On-site, Secondary: Online) |
Smoothing methods for reducing false positives in performance anomaly detection using machine learning Taku Wakui, Mineyoshi Masuda (Hitachi) KBSE2022-41 SC2022-36 |
In the integrated infrastructure management market, ML-based anomaly detection is one of the key features. However, comp... [more] |
KBSE2022-41 SC2022-36 pp.60-65 |
RISING (3rd) |
2022-10-31 10:30 |
Kyoto |
Kyoto Terrsa (Day 1), and Online (Day 2, 3) |
[Poster Presentation]
Study of Data Collection System for Anomaly Detection by Ultrasonic Components of Mechanical Equipment Operating Sounds Rio Shigyo, Daiki Nobayashi, Kazuya Tsukamoto, Mitsunori Mizumachi, Takeshi Ikenaga (KIT) |
Status checks of mechanical equipment are typically being conducted by workers (manpower) at the actual place. However, ... [more] |
|
RISING (3rd) |
2022-10-31 13:00 |
Kyoto |
Kyoto Terrsa (Day 1), and Online (Day 2, 3) |
[Poster Presentation]
Network Anomaly Detection Method Based on Communication Volume Changes in Edge Switches Yuya Nakanishi, Shingo Ata (Osaka City Univ.) |
Early detection of failures and anomalies that occur in the network and prompt recovery processing are essential for sta... [more] |
|
NS |
2022-10-05 15:10 |
Hokkaido |
Hokkaidou University + Online (Primary: On-site, Secondary: Online) |
An Anomaly Detection System of IoT Traffic for Smart Home Environments Naoto Watanabe, Taku Yamazaki, Takumi Miyoshi (Shibaura Inst. Tech.), Ryo Yamamoto (UEC) NS2022-83 |
With the proliferation of Internet of things (IoT) devices, cyberattacks targeting these devices have also been increasi... [more] |
NS2022-83 pp.8-11 |
IA, CQ, MIKA (Joint) |
2022-09-16 15:45 |
Hokkaido |
Hokkaido Citizens Actives Center (Primary: On-site, Secondary: Online) |
Study of Data Collection System for Ultrasonic Waves Based Anomaly Detection of Mechanical Equipment Rio Shigyo, Daiki Nobayashi, Kazuya Tsukamoto, Mitsunori Mizumachi, Takeshi Ikenaga (KIT) IA2022-32 |
Status checks of mechanical equipment are typically being conducted by workers (manpower). However, since the check timi... [more] |
IA2022-32 pp.97-102 |
ITE-ME, EMM, IE, LOIS, IEE-CMN, IPSJ-AVM [detail] |
2022-09-13 13:40 |
Online |
Keio Univ. Yagami Campus (Hybrid) (Primary: Online, Secondary: On-site) |
Video Anomaly Detection Method using Deep Learning Models and Crowd Workers Ryuya Itano, Tomoya Nohara, Takahiro Koita (Doshisha Univ.) LOIS2022-10 IE2022-32 EMM2022-38 |
In recent years, the number of surveillance cameras installed has been increasing due to the spread of IoT. However, thi... [more] |
LOIS2022-10 IE2022-32 EMM2022-38 pp.1-6 |
KBSE, SWIM |
2022-05-20 15:00 |
Tokyo |
(Primary: On-site, Secondary: Online) |
Practical Application of Self-Adaptive Anomaly Detection Method Using XAI Shimon Sumita, Hiroyuki Nakagawa, Tatsuhiro Tsuchiya (Osaka Univ.) KBSE2022-3 SWIM2022-3 |
In this study, we examine the use of XAI to improve the performance of a self-adaptive anomaly detection method. As a sp... [more] |
KBSE2022-3 SWIM2022-3 pp.13-18 |
ICM, IPSJ-CSEC, IPSJ-IOT |
2022-05-19 10:25 |
Nagano |
(Primary: On-site, Secondary: Online) |
BGP Hijacking Detection Using Deep Learning Kenta Nakashima, Mitiko Harayama (Gifu City Univ) ICM2022-2 |
Failures of large autonomous systems (ASs) and network attacks can affect Border Gateway Protocol (BGP) messages, causin... [more] |
ICM2022-2 pp.6-11 |