Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
NS, IN (Joint) |
2024-02-29 09:20 |
Okinawa |
Okinawa Convention Center |
Intrusion Detection System Based on Federated Decision Trees Naoto Watanabe, Taku Yamazaki, Takumi Miyoshi (Shibaura Inst. Tech.), Masataka Nakahara, Norihiro Okui, Ayumu Kubota (KDDI Research) NS2023-190 |
With the proliferation of Internet of things (IoT) devices, cyberattacks targeting these devices have also been increasi... [more] |
NS2023-190 pp.109-112 |
RISING (3rd) |
2023-10-31 13:00 |
Hokkaido |
Kaderu 2・7 (Sapporo) |
|
(To be available after the conference date) [more] |
|
CPSY, DC, IPSJ-ARC [detail] |
2023-06-05 14:10 |
Ehime |
Nigitatsu-Kaikan (Primary: On-site, Secondary: Online) |
Load Balancer for Parallel NIDS Using Multiple Devices with Diferrent Processing Performance Hayato Yamaki, Shinobu Miwa, Hiroki Honda (UEC) CPSY2023-2 DC2023-2 |
(To be available after the conference date) [more] |
CPSY2023-2 DC2023-2 pp.2-7 |
NS |
2023-05-12 10:00 |
Tokyo |
Shinjuku Campus, Kogakuin University + Online (Primary: On-site, Secondary: Online) |
On Kernel Networking Using extended Berkeley Packet Filter Empowered by Neural Networks Takanori Hara (NAIST), Masahiro Sasabe (Kansai Univ.) NS2023-15 |
extended Berkeley Packet Filter (eBPF) is a technology to control a Linux kernel through an arbitrary program. It has be... [more] |
NS2023-15 pp.26-31 |
ICSS, IPSJ-SPT |
2023-03-13 14:40 |
Okinawa |
Okinawaken Seinenkaikan (Primary: On-site, Secondary: Online) |
Consideration of a Packet Level Anomaly Communication Classification Model Using Word Embedding and LSTM Yoshikatsu Kashiwabara, Kohei Miyamoto, Iida Masazumi, Shota Kawanaka (Kyushu Univ), Han Chansu, Ban Tao, Kenshi Takahashi (NICT), Jun'ichi Takeuchi (Kyushu Univ) ICSS2022-53 |
In recent years, network-based intrusion detection systems (NIDS), which are systems for detecting unauthorized access o... [more] |
ICSS2022-53 pp.31-36 |
ICSS, IPSJ-SPT |
2023-03-13 15:20 |
Okinawa |
Okinawaken Seinenkaikan (Primary: On-site, Secondary: Online) |
Multimodal Feature Integration Toward High-Accuracy Network Intrusion Detection Masazumi Iida, Kohei Miyamoto, Yoshinari Takeishi, Shota Kawanaka (Kyushu Univ.), Chansu Han, Tao Ban, Takeshi Takahashi (NICT), Jun'ichi Takeuchi (Kyushu Univ.) ICSS2022-55 |
(To be available after the conference date) [more] |
ICSS2022-55 pp.43-48 |
NS, IN (Joint) |
2022-03-10 11:00 |
Online |
Online |
Experimental Evaluation of Influence of Distributing Deep Learning-Based IDSs on Their Classification Accuracy and Explainability Ayaka Oki, Yukio Ogawa, Kaoru Ota, Mianxiong Dong (Muroran-IT) IN2021-33 |
Increased data traffic associated with the wide spread usage of IoT devices accentuates the risk of large-scale cyber at... [more] |
IN2021-33 pp.13-18 |
CQ, IMQ, MVE, IE (Joint) [detail] |
2022-03-09 09:55 |
Online |
Online (Zoom) |
Active intrusion detection method for IoT devices Takahiro Ohtani, Ryo Yamamoto, Satoshi Ohzahata (UEC) CQ2021-101 |
In recent years, the threat of attacks against IoT (Internet of Things) devices has become apparent with the rapid sprea... [more] |
CQ2021-101 pp.5-10 |
VLD, DC, RECONF, ICD, IPSJ-SLDM (Joint) [detail] |
2021-12-01 10:10 |
Online |
Online |
A Multilayer Perceptron Training Accelerator using Systolic Array Takeshi Senoo, Akira Jinguji, Ryosuke Kuramochi, Hiroki Nakahara (Toyko Tech) VLD2021-23 ICD2021-33 DC2021-29 RECONF2021-31 |
Neural networks are being used in various applications, and the demand for fast training with large amounts of data is e... [more] |
VLD2021-23 ICD2021-33 DC2021-29 RECONF2021-31 pp.37-42 |
IN, NS, CS, NV (Joint) |
2021-09-09 14:05 |
Online |
Online |
A Machine Learning Based Network Intrusion Detection System with Appling Different Algorithms in Multiple Stages Seiichi Sasa, Hiroyuki Suzuki, Akio Koyama (Yamagata Univ.) NS2021-63 |
In recent years, the rapid development of Information and Communication Technology (ICT) has led to the provision of a w... [more] |
NS2021-63 pp.36-41 |
ICSS, IPSJ-SPT |
2021-03-01 09:10 |
Online |
Online |
Developing and Characterizing a New Approach to Extracting Communication Sessions Associated with NIDS Alerts Ryosuke Ishibashi, Hiroki Goto (Kyushu Univ.), Chansu Han, Tao Ban, Takeshi Takahashi (NICT), Jun'ichi Takeuchi (Kyushu Univ.) ICSS2020-26 |
(To be available after the conference date) [more] |
ICSS2020-26 pp.1-6 |
CPSY, RECONF, VLD, IPSJ-ARC, IPSJ-SLDM [detail] |
2021-01-26 10:55 |
Online |
Online |
Network Intrusion Detection System based on Hybrid FPGA/GPU Pattern Matching Shunta Kikuchi (AIST/The Univ. of Tokyo), Tsutomu Ikegami, Akram ben Ahmed (AIST), Tomohiro Kudoh (The Univ. of Tokyo/AIST), Ryohei Kobayashi, Norihisa Fujita, Taisuke Boku (Univ. of Tsukuba) VLD2020-59 CPSY2020-42 RECONF2020-78 |
These days, Heterogeneous computing is becoming common. In this study, we made an NIDS (Network Intrusion Detection Syst... [more] |
VLD2020-59 CPSY2020-42 RECONF2020-78 pp.113-118 |
SeMI, IPSJ-ITS, IPSJ-MBL, IPSJ-DPS (Joint) |
2020-06-18 13:00 |
Online |
Online |
A Prototype and Evaluation of Vibration Detection System for Surveillance of Deer Fence Takuya Kato (KDDI Research, Inc.), Hiroyuki Yokota (TIRI), Yuichiro Hei, Izuru Nogaito, Eiji Utsunomiya (KDDI Research, Inc.) SeMI2020-1 |
Deer fences are widely used as an effective means of preventing serious feeding damage by deer and other wildlife. If de... [more] |
SeMI2020-1 pp.1-6 |
HWS, VLD [detail] |
2020-03-06 17:15 |
Okinawa |
Okinawa Ken Seinen Kaikan (Cancelled but technical report was issued) |
Circuit Architecture Exploration for Optical Neural Network based on Integrated Nanophotonics Naoki Hattori, Yutaka Masuda, Tohru Ishihara (Nagoya Univ.), Jun Shiomi (Kyoto Univ.), Akihiko Shinya, Masaya Notomi (NTT) VLD2019-137 HWS2019-110 |
With a rapid progress of the integrated nanophotonics technology, optical neural networks
based on the integrated nano... [more] |
VLD2019-137 HWS2019-110 pp.251-256 |
SeMI, IPSJ-ITS, IPSJ-MBL, IPSJ-DPS |
2019-05-24 11:50 |
Kagoshima |
Amami-shi Syakai Fukushi Center |
Impact Detection for Polyethylene Net Animal Guard Fencing Takuya Kato, Izuru Nogaito, Eiji Utsunomiya (KDDI Research, Inc.) SeMI2019-13 |
Animal guard fencing is a way of the effective prevention of harmful wild animals which cause nearly twenty billion yen ... [more] |
SeMI2019-13 pp.177-181 |
IN, NS (Joint) |
2019-03-04 09:00 |
Okinawa |
Okinawa Convention Center |
Intrusion Detection System using semi-supervised learning with Adversarial Autoencoder Kazuki Hara, Kohei Shiomoto (Tokyo City Univ.) NS2018-193 |
In recent years the importance of intrusion detection system(IDS) is increasing. In particular, a method using machine l... [more] |
NS2018-193 pp.1-6 |
SITE, IPSJ-EIP |
2018-06-01 14:45 |
Kanagawa |
|
Implementation and Evaluation of Intrusion Detection System for Malicious PC by Sensor Hosts Hiroaki Kuno, Satoshi Kimura, Hiroyuki Inaba (KIT) SITE2018-4 |
In recent years, Intrusion Detection System(IDS) is not able to catch the unknown attack
as malware and its variant ar... [more] |
SITE2018-4 pp.95-99 |
VLD, HWS (Joint) |
2018-02-28 09:55 |
Okinawa |
Okinawa Seinen Kaikan |
On Memory Size Reduction of Programmable Hardware for Random Forest based Network Intrusion Detection Binbin Xue, Shinobu Nagayama, Masato Inagi, Shin'ichi Wakabayashi (Hiroshima City Univ.) VLD2017-90 |
In our previous research, we proposed dedicated programmable hardware of random forest based NIDSs. In this research, we... [more] |
VLD2017-90 pp.7-12 |
SIP, CAS, MSS, VLD |
2017-06-19 11:40 |
Niigata |
Niigata University, Ikarashi Campus |
An Implementation Method of Reconfigurable Network Intrusion Detection Systems Based on Random Forests Binbin Xue, Shinobu Nagayama, Masato Inagi, Shin'ichi Wakabayashi (Hiroshima City Univ.) CAS2017-7 VLD2017-10 SIP2017-31 MSS2017-7 |
In this paper, we propose an implementation method of reconfigurable network intrusion detection system based on random ... [more] |
CAS2017-7 VLD2017-10 SIP2017-31 MSS2017-7 pp.37-42 |
NLP |
2017-05-12 11:00 |
Okayama |
Okayama University of Science |
Investigation of Fast Construction for Intrusion Detection System using Multi-Layer Extreme Learning Machine. Daichi Noguchi, Masaharu Adachi (Tokyo Denki Univ.) NLP2017-18 |
Recently, there are incremental threats of cyber security for holding the Olympic Games in Tokyo in 2020. The fast const... [more] |
NLP2017-18 pp.87-92 |