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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| ICSS, IPSJ-SPT | 2024-03-21 16:10 |
Okinawa | OIST (Primary: On-site, Secondary: Online) |
Considerations on Differential Privacy Mechanisms in MNIST Naoki Kawahara, Pengxuan Wei, Ryunosuke Higashi, Kenta Okada, Tatsuhiro Yamatsuki, Atsuko Miyaji (Osaka Univ.)  ICSS2023-79 |
In recent years, data utilization technologies, including machine learning, have been steadily advancing. One means of p... [more] | ICSS2023-79 pp.71-78 |
| ICM, NS, CQ, NV (Joint) |
2023-11-22 15:00 |
Ehime | Ehime Prefecture Gender Equality Center (Primary: On-site, Secondary: Online) |
A Study on the Publish-Subscribe-based IoT Communication Protocol Considering Differential Privacy Reiya Shimamoto, Kauzya Sakai (TMU) NS2023-123 |
The development of IoT devices has been remarkable in recent years, and these devices are now used in many applications ... [more] | NS2023-123 pp.74-77 |
| NS | 2023-10-06 15:20 |
Hokkaido | Hokkaidou University + Online (Primary: On-site, Secondary: Online) |
Incentive Mechanism Considering Heterogeneous Privacy Demand Level in Federated Learning with Differential Privacy Shota Miyagoshi, Takuji Tachibana (Univ. Fukui) NS2023-104 |
In federated learning, where multiple data owners participate as clients to perform machine learning, each client shares... [more] | NS2023-104 pp.162-167 |
| AI | 2023-09-12 14:35 |
Hokkaido | Proposal of effective location information privacy protection method using measurement equipment error Riho Isawa, Yuichi Sei, Yasuyuki Tahara, Akihiko Ahsuga (UEC) AI2023-15 |
In recent years, systems that publicly share statistical data based on people's location information, such as congestion... [more] | AI2023-15 pp.77-82 |
|
| RCC, ISEC, IT, WBS | 2023-03-14 10:30 |
Yamaguchi | (Primary: On-site, Secondary: Online) |
[Invited Talk]
Information-Theoretic Analyses for Two Problems Taking Security into Consideration
-- Parameter Estimation Problem under Local Differential Privacy, and Privacy-Utility Tradeoff Problem -- Shota Saito (Gunma Univ.) IT2022-71 ISEC2022-50 WBS2022-68 RCC2022-68 |
This lecture surveys the following two problems: 1) parameter estimation problem under $(epsilon, delta)$-local differen... [more] | IT2022-71 ISEC2022-50 WBS2022-68 RCC2022-68 pp.19-24 |
| RCC, ISEC, IT, WBS | 2023-03-14 16:50 |
Yamaguchi | (Primary: On-site, Secondary: Online) |
Proposal for a privacy-preserving frequency estimation method Naoki Kawahara, Atsuko Miyaji (Osaka Univ.), Tomoaki Mimoto (ATR) IT2022-97 ISEC2022-76 WBS2022-94 RCC2022-94 |
Differential privacy is one of the methods used to protect personal data by adding noise to personal data and its analys... [more] | IT2022-97 ISEC2022-76 WBS2022-94 RCC2022-94 pp.187-194 |
| NS, ICM, CQ, NV (Joint) |
2022-11-24 09:55 |
Fukuoka | Humanities and Social Sciences Center, Fukuoka Univ. + Online (Primary: On-site, Secondary: Online) |
Highly Accurate Privacy-Enhanced Federated Learning Using Data On The Server Yuta Kakizaki (TUS), Koya Sato (UEC), Keiichi Iwamura (TUS) NS2022-100 |
Federated learning is a cooperative machine learning approach that prohibits disclosing training data from distributed d... [more] | NS2022-100 pp.1-6 |
| NS, ICM, CQ, NV (Joint) |
2022-11-24 10:20 |
Fukuoka | Humanities and Social Sciences Center, Fukuoka Univ. + Online (Primary: On-site, Secondary: Online) |
Social Surplus Maximization Using Incentive Mechanism for Cross-Silo Federated Learning with Differential Privacy Shota Miyagoshi, Takuji Tachibana (Univ. Fukui) NS2022-101 |
In cross-silo federated learning, where multiple organizations participate, the prediction accuracy of the global model ... [more] | NS2022-101 pp.7-12 |
| NS, SR, RCS, SeMI, RCC (Joint) |
2022-07-14 14:00 |
Ishikawa | The Kanazawa Theatre + Online (Primary: On-site, Secondary: Online) |
A Study of Dynamic Privacy Control Method in LDP for Preserving Temporal/Spatial Intrinsic Information Value of Trajectory Data Taisho Sasada, Yuzo Taenaka, Youki Kadobayashi (NAIST) NS2022-47 |
Spatiotemporal data, including people's movement trajectories and transit points, is highly valuable for various applica... [more] | NS2022-47 pp.106-111 |
| RISING (3rd) |
2021-11-17 09:00 |
Tokyo | (Primary: On-site, Secondary: Online) |
Proposal of Incentive Mechanism for Cross-Silo Federated Learning with Differential Privacy Shota Miyagoshi, Takuji Tachibana (Univ. Fukui) |
In cross-silo federated learning, where multiple companies/organizations participate, the prediction accuracy of the glo... [more] | |
| RCS, SR, NS, SeMI, RCC (Joint) |
2021-07-16 10:55 |
Online | Online | A Study on Decentralized Machine Learning with Differential Privacy based on Input Perturbation Masakazu Okamoto, Koya Sato, Keiichi Iwamura (Tokyo Univ. of Science) SR2021-34 |
Distributed machine learning eliminates the need for users to disclose their data to the out of the terminal since train... [more] | SR2021-34 pp.67-72 |
| RCS, SR, NS, SeMI, RCC (Joint) |
2021-07-16 13:25 |
Online | Online | An Evaluation of Learning Accuracy in Federated Learning with Local Differential Privacy Yuta Kakizaki, Koya Sato, Keiichi Iwamura (Tokyo Univ. of Science) SR2021-37 |
In federated learning, where each device learns cooperatively without disclosing the training data, the privacy level ca... [more] | SR2021-37 pp.87-93 |
| LOIS, ISEC, SITE | 2020-11-06 14:40 |
Online | Online | Considering the variation of the noise-addition amount in local differential privacy with user trajectory adjacency Taisho Sasada, Yuzo Taenaka, Youki Kadobayashi, Doudou Fall (NAIST) ISEC2020-39 SITE2020-36 LOIS2020-19 |
The detection of clusters in densely populated areas by contact tracing is urgent, because these locations are trajector... [more] | ISEC2020-39 SITE2020-36 LOIS2020-19 pp.45-50 |
| ISEC, IT, WBS | 2020-03-10 13:50 |
Hyogo | University of Hyogo (Cancelled but technical report was issued) |
A Statistical Decision-Theoretic Approach for Measuring Privacy Risk in Information Disclosure Problem Alisa Miyashita, Akira Kamatsuka (Waseda Univ.), Takahiro Yoshida (Yokohama College of Commerce), Toshiyasu Matsushima (Waseda Univ.) IT2019-104 ISEC2019-100 WBS2019-53 |
In this paper, we deal with the problem of database statistics publishing with privacy and utility guarantees. While var... [more] | IT2019-104 ISEC2019-100 WBS2019-53 pp.95-100 |
| IBISML | 2018-11-05 15:10 |
Hokkaido | Hokkaido Citizens Activites Center (Kaderu 2.7) | [Poster Presentation]
Differential Privacy for Likelihood Ratio Test Arashi Haishima (Univ. of Tsukuba), Jun Sakuma (Univ. of Tsukuba/RIKEN) IBISML2018-86 |
Likelihood ratio test of logistic regression commonly used when testing whether an attribute of data significantly influ... [more] | IBISML2018-86 pp.313-320 |
| PRMU, BioX | 2017-03-20 14:10 |
Aichi | [Invited Talk]
Recent Technology Trends in Location Privacy Takao Murakami (AIST) BioX2016-42 PRMU2016-205 |
With the widespread use of smart phones and in-car navigation systems, people are increasingly using LBS (Location-based... [more] | BioX2016-42 PRMU2016-205 pp.51-56 |
|
| DC, SS | 2016-10-27 14:05 |
Shiga | Hikone Kinro-Fukushi Kaikan Bldg. | Note on Data Aggregation on Smart Grid Communications Considering Fault Tolerance and Privacy Ryota Ogasawara, Masayuki Arai (Nihon Univ.) SS2016-23 DC2016-25 |
In smart grid communications it is important to aggregate users' usage data while preserving privacy. In this paper we p... [more] | SS2016-23 DC2016-25 pp.31-36 |
| NC, IPSJ-BIO, IBISML, IPSJ-MPS (Joint) [detail] |
2015-06-23 13:00 |
Okinawa | Okinawa Institute of Science and Technology | Differential Privacy and Pseudo-Bayesian Posterior Kentaro Minami, Hiromi Arai, Issei Sato, Hiroshi Nakagawa (The University of Tokyo) IBISML2015-7 |
We investigate relationship between differential privacy and pseudo-Bayesian posterior distributions. Recently, Wang, et... [more] | IBISML2015-7 pp.39-46 |
| NC, IPSJ-BIO, IBISML, IPSJ-MPS (Joint) [detail] |
2015-06-23 13:25 |
Okinawa | Okinawa Institute of Science and Technology | Differentially Private Multiple Hypothesis Testing Kazuya Kakizaki, Jun Sakuma (Tsukuba Univ.) IBISML2015-8 |
Statistical hypothesis testing using test statistics ($p$-value) are commonly used for identification of new scientific ... [more] | IBISML2015-8 pp.47-54 |
| SS | 2015-05-11 14:25 |
Kumamoto | Kumamoto University | [Invited Lecture]
Quantitative Information Flow and Differential Privacy Hiroyuki Seki (Nagoya Univ.) SS2015-4 |
Recently, quantitative modellings for security and privacy have been paid much attention. Among them are quantitative in... [more] | SS2015-4 pp.17-22 |
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