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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| KBSE | 2024-03-14 17:10 |
Okinawa | Okinawa Prefectual General Welfare Center (Primary: On-site, Secondary: Online) |
Reusable Self-Adaptive Intrusion Recovery for Cloud Native Applications Takumi Ikeda, Takuto Yamauchi (Waseda Univ.), Kenji Tei (Tokyo Tech)  KBSE2023-79 |
Research is being conducted on self-adaptive technologies that monitor, analyze, plan and execute adaptive actions at ru... [more] | KBSE2023-79 pp.79-81 |
| 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 |
| MSS, CAS, IPSJ-AL [detail] | 2023-11-17 14:45 |
Okinawa | Construction of criminal models using kernel density estimation Kenta Sakakura, Eiji Konaka (Meijo Univ.) CAS2023-80 MSS2023-50 |
Since the 2000s, security systems using autonomous mobile vehicles have begun to be put into practical use, and automati... [more] | CAS2023-80 MSS2023-50 pp.107-112 |
|
| 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 |
| R | 2022-10-07 15:15 |
Fukuoka | (Primary: On-site, Secondary: Online) |
A Note on Pull-Type Security Patch Management Policies for Intrusion Tolerant Systems Junjun Zheng (Osaka Univ.), Hiroyuki Okamura, Tadashi Dohi (Hiroshima Univ.) R2022-37 |
This paper considers the pull-type security patch management policies for intrusion tolerant systems. A composite stocha... [more] | R2022-37 pp.31-36 |
| 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 |
| R | 2022-06-16 14:50 |
Online | Online | A Note on Interval Reliability Analysis of Intrusion Tolerant Systems Subject to DoS Attacks Junjun Zheng (Ritsumeikan Univ.), Hiroyuki Okamura, Tadashi Dohi (Hiroshima Univ.) R2022-8 |
This paper focuses on the transient behavior of intrusion tolerant systems with preventive maintenance subject to DoS (D... [more] | R2022-8 pp.13-18 |
| MSS, NLP | 2022-03-29 10:45 |
Online | Online | A proposal of method for defending against cyber attacks by combining honeypots and IPS Yudai Yamamoto, Shingo Yamaguchi (Yamaguchi Univ.) MSS2021-71 NLP2021-142 |
We propose a defense system that makes it possible to detect and prevent attacks targeting web applications and IoT devi... [more] | MSS2021-71 NLP2021-142 pp.83-88 |
| 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 |
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