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 |
RECONF, VLD |
2024-01-30 14:50 |
Kanagawa |
AIRBIC Meeting Room 1-4 (Primary: On-site, Secondary: Online) |
FPGA-Accelerated Random Forest for Real-Time IoT Intrusion Detection Qingyu Zeng, Yuko Hara (Tokyo Tech) VLD2023-97 RECONF2023-100 |
The rapid proliferation of the Internet of Things (IoT) has heightened cyber security concerns, necessitating efficient ... [more] |
VLD2023-97 RECONF2023-100 pp.99-104 |
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 |
HWS, ICD |
2022-10-25 17:05 |
Shiga |
(Primary: On-site, Secondary: Online) |
How to Identify the Physical Direction of CAN Message Transmission Yosuke Maekawa, Camille Gay (TOYOTA/YNU), Tsutomu Matsumoto (YNU) HWS2022-43 ICD2022-35 |
The impact of cyber-attacks on automobiles is becoming more serious as vehicles become more connected and multi-function... [more] |
HWS2022-43 ICD2022-35 pp.76-81 |
IT |
2022-07-22 10:50 |
Okayama |
Okayama University of Science (Primary: On-site, Secondary: Online) |
A study on deep learning-based cyber attack detection Ruei-Fong Hong, Qiangfu Zhao (UoA), Shih-Cheng Horng (CYUT) IT2022-22 |
Cyberattack is a broad term for cybercrime that includes any deliberate attack on a computer device, network or infrastr... [more] |
IT2022-22 pp.36-41 |
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 |
RISING (3rd) |
2021-11-16 09:30 |
Tokyo |
(Primary: On-site, Secondary: Online) |
On Attack Pattern Classification in IoT Networks for Network Intrusion Detection Systems Jesse Atuhurra, Takanori Hara (NAIST), Yuanyu Zhang (Xidian Univ.), Shoji Kasahara (NAIST) |
With the proliferation of IoT devices, IoT security problems arise. To protect heterogeneous connected devices in IoT ne... [more] |
|
IA |
2021-10-15 16:50 |
Online |
Online |
Malware Traffic Detection at Certain Time Using IP Flow Information Seiya Komatsu, Yusei Katsura, Masatoshi Kakiuchi, Ismail Arai, Kazutoshi Fujikawa (NAIST) IA2021-27 |
The damage caused by the activities of malware such as botnets and ransomware has become a social problem. In order to d... [more] |
IA2021-27 pp.6-11 |
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 |
IN, NS (Joint) |
2021-03-05 10:10 |
Online |
Online |
A Convolutional Autoencoder Based Method for Cyber Intrusion Detection Xinyi She, Yuji Sekiya (Tokyo Univ.) IN2020-77 |
Cyber intrusion detection systems are increasingly crucial due to the monumental growth of internet applications. Howeve... [more] |
IN2020-77 pp.138-143 |
IA, IN (Joint) |
2020-12-15 10:50 |
Online |
Online |
Development of an Intrusion Detection System Utilizing Social Network Analysis Principles James Lu, Yuji Sekiya (Univ. of Tokyo) IA2020-29 |
As computer networks grow increasingly complex and cyberattacks become more sophisticated, better methods are needed to ... [more] |
IA2020-29 pp.18-21 |
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 |
IN, NS, CS, NV (Joint) |
2018-09-07 09:20 |
Miyagi |
Research Institute of Electrical Communication, Tohoku Univ. |
A Consideration of Evaluation Dataset for Malware Detection System Hisashi Takahara (UNP) IN2018-33 |
Today, while internet cyber-attacks are increasing, protection against the cyber-attacks have become indispensable. Amon... [more] |
IN2018-33 pp.65-69 |
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 |