| Project/Area Number |
20K19801
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| Research Category |
Grant-in-Aid for Early-Career Scientists
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| Allocation Type | Multi-year Fund |
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| Review Section |
Basic Section 60070:Information security-related
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| Research Institution | Toyo University |
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Principal Investigator |
ZHU Jinxiao 東洋大学, 情報連携学部, 助教 (30754329)
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| Project Period (FY) |
2020-04-01 – 2023-03-31
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| Project Status |
Completed (Fiscal Year 2022)
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| Budget Amount *help |
¥4,160,000 (Direct Cost: ¥3,200,000、Indirect Cost: ¥960,000)
Fiscal Year 2021: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2020: ¥2,600,000 (Direct Cost: ¥2,000,000、Indirect Cost: ¥600,000)
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| Keywords | 物理層認証 / 無線通信 / セキュリティ / デバイス識別 / authentication / radiometric feature / device identification / wireless communication / physical layer security / physical layer / visibility graph / identification / fractal dimension / PLA / RF Feature / USRP / IoT / Authentication |
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| Outline of Research at the Start |
This project will study a novel physical layer authentication (PLA) scheme to enhance the authentication ability of communication systems and protect IoT systems against security attacks, such as impersonation attack. The study will be conducted from both experimental and theoretical aspects. Particularly, in the first year, I will construct an experiment testbed and collect data of radio frequency feature from various wireless devices; in the second year, I will extract the raw data, then conduct statistical analysis to explore new features and design novel PLA schemes.
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| Outline of Final Research Achievements |
With the wide application of internet of things (IoT), setting up an effective authentication system in those networks becomes overwhelming difficult yet urgent. To solve the authentication issue, this project focused on studying radiometric features generated by wireless devices for device authentication from both experimental and theoretical aspects. Specifically, we constructed an experiment system, collected raw radiometric feature data of wireless devices from the system, and designed several identification schemes with the data for device authentication. About the identification schemes, we explored two main approaches: identification with hand-crafted radiometric feature and identification with automatically-generated radiometric feature by deep learning algorithms. Finally, the efficiency of the proposed identification schemes have been verified by experiment and simulation studies.
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| Academic Significance and Societal Importance of the Research Achievements |
本研究の目的は，IoTネットワークにおける無線機器認証の課題を解決することである．従来の認証方法では，無線機器の身分情報を暗号鍵で暗号化して認証を行っていましたが，IoTでは膨大な数の無線機器に対して鍵の配布や管理が非常に困難である．本研究では，暗号鍵を使わない物理層認証方法を研究した．具体的には，実験システムを構築し，人間の指紋のようなデバイス指紋を研究開発して実験システムでその有効性を示した．
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