Project/Area Number |
26330085
|
Research Category |
Grant-in-Aid for Scientific Research (C)
|
Allocation Type | Multi-year Fund |
Section | 一般 |
Research Field |
Software
|
Research Institution | Osaka University |
Principal Investigator |
Nakagawa Ikuo 大阪大学, サイバーメディアセンター, 招へい准教授 (70647437)
|
Co-Investigator(Kenkyū-buntansha) |
下條 真司 大阪大学, サイバーメディアセンター, 教授 (00187478)
樋地 正浩 東北大学, 経済学研究科, 教授 (40400212)
福本 昌弘 高知工科大学, 情報学群, 教授 (70299387)
菊池 豊 高知工科大学, 地域連携機構, 教授 (80242288)
|
Project Period (FY) |
2014-04-01 – 2017-03-31
|
Project Status |
Completed (Fiscal Year 2016)
|
Budget Amount *help |
¥4,810,000 (Direct Cost: ¥3,700,000、Indirect Cost: ¥1,110,000)
Fiscal Year 2016: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2015: ¥2,210,000 (Direct Cost: ¥1,700,000、Indirect Cost: ¥510,000)
Fiscal Year 2014: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
|
Keywords | IoT / Intercloud / Statistical Computation / Privacy Preserving / Internet of Things / Cloud Computing / Distributed Computing / Statistical Computing / インタークラウド / ビッグデータ / 分散秘匿分析 |
Outline of Final Research Achievements |
In this research, we proposed distributed privacy preserving statistical computation mechanism for processing a huge amount of IoT sensor data, where we reduce the risk of revealing privacy data while we would use scalable, elastic and cost effective computing power of public cloud. In the mechanism, IoT devices upload their data into multiple cloud computing environment with privacy preserving technique so that it reduce the risk of privacy data, while we would achieve accurate statistical indices. We designed and implemented prototype system for the mechanism and proved its effectiveness. We also extended the mechanism to be scalable and resilient with DHT and distributed transaction technique. We proposed to apply our mechanism for some business cases, such as smart home, healthcare or online voting. We designed and implemented the prototype for the case of smart home, as well.
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