Chen, Yin

写真a

Affiliation

Graduate School of Media and Governance (Shonan Fujisawa)

Position

Project Associate Professor (Non-tenured)

Related Websites

Profile 【 Display / hide

  • Yin Chen received the B.S. and M.S. degrees from the School of Computer Science and Technology, Xidian University, Xi’an, China, in 2008 and 2011, respectively, and the Ph.D. degree from the School of Systems Information Science, Future University Hakodate, Japan, in 2014. From April to October 2014, he was a Postdoctoral Researcher with Future University Hakodate. He is currently serving as a Senior Research Assistant Professor with the Graduate School of Media and Governance, Keio University, Fujisawa, Japan. His research interests are in the wide area of wireless communication and networks and their applications in the IoT and smart cities. He is a member of IEEE, ACM and IPSJ.

Career 【 Display / hide

  • 2014.11
    -
    2018.10

    Keio University, Graduate School of Media and Governance, Research Assistant Professor

  • 2018.11
    -
    Present

    Keio University, Graduate School of Media and Governance, Senior Research Assistant Professor

Academic Background 【 Display / hide

  • 2004.08
    -
    2008.07

    Xidian University, School of Computer Science and Technology, Computer Science

    China, University, Graduated

  • 2008.08
    -
    2011.03

    Xidian University, Graduate School of Computer Science and Technology, Computer Science

    China, Graduate School, Completed, Master's course

  • 2011.04
    -
    2014.03

    FUTURE UNIVERSITY-HAKODATE, Graduate School of Systems Information Science, Systems Information Science

    Graduate School, Completed, Doctoral course

Academic Degrees 【 Display / hide

  • Master, Xidian University, Dissertation, 2011.03

  • PhD (System Information Science), FUTURE UNIVERSITY-HAKODATE, Dissertation, 2014.03

    Exact throughput capacity studies for mobile ad hoc networks

Licenses and Qualifications 【 Display / hide

  • TOIEC 925点 , 2014

  • 日本語能力試験1級, 2019.07

 

Research Areas 【 Display / hide

  • Informatics / Information network

Research Keywords 【 Display / hide

  • Urban Sensing

  • Stochastic Modelling

  • Wireless Networks

  • Wireless Sensor Networks

 

Papers 【 Display / hide

  • Visibility graph entropy based radiometric feature for physical layer identification

    Zeng S., Chen Y., Li X., Zhu J., Shen Y., Shiratori N.

    Ad Hoc Networks (Elsevier)  127 2022.03

    Research paper (scientific journal), Joint Work, Accepted,  ISSN  15708705

     View Summary

    Emerging physical layer identification methods have demonstrated the capability to complement and enhance the device authentication of Internet of Things networks by exploiting the uncontrollable, unclonable, and unforgeable radiometric features resulted from randomly generated hardware imperfection in wireless devices. Multiple feature-based identification has proven an efficient and feasible approach to improving identification performance. At the same time, the lack of radiometric features effective for device identification is a major problem. Most of the existing features are derived from the view of the time, frequency, or phase domain. In this study, we explore the graph domain of wireless frame's preambles and propose a new radiometric feature called normalized horizontal visibility graph Shannon entropy (HVGE). At first, we introduce a preprocessing consisting of sample truncation and downsampling to enable the adjustment between the computational time of visibility graph (VG) conversion and the identification performance. Secondly, we propose the calculation method of the new HVGE feature from the VG representation. Finally, an experimental study using 50 off-the-shelf wireless devices was conducted to investigate the impact of the preprocessing parameters and the effect of noise and feature combinations on the identification performance gain.

  • Rppuf: An ultra-lightweight reconfigurable pico-physically unclonable function for resource-constrained iot devices

    Huang Z., Li L., Chen Y., Li Z., Wang Q., Jiang X.

    Electronics (Switzerland) (MDPI)  10 ( 23 )  2021.12

    Research paper (scientific journal), Joint Work, Accepted

     View Summary

    With the advancement of the Internet of Things (IoTs) technology, security issues have received an increasing amount of attention. Since IoT devices are typically resource-limited, con-ventional security solutions, such as classical cryptography, are no longer applicable. A physically unclonable function (PUF) is a hardware-based, low-cost alternative solution to provide security for IoT devices. It utilizes the inherent nature of hardware to generate a random and unpredictable fingerprint to uniquely identify an IoT device. However, despite existing PUFs having exhibited a good performance, they are not suitable for effective application on resource-constrained IoT devices due to the limited number of challenge-response pairs (CRPs) generated per unit area and the large hardware resources overhead. To solve these problems, this article presents an ultra-lightweight reconfigurable PUF solution, which is named RPPUF. Our method is built on pico-PUF (PPUF). By incorporating configurable logics, one single RPPUF can be instantiated into multiple samples through configurable information K. We implement and verify our design on the Xilinx Spartan-6 field programmable gate array (FPGA) microboards. The experimental results demonstrate that, compared to previous work, our method increases the uniqueness, reliability and uniformity by up to 4.13%, 16.98% and 10.5%, respectively, while dramatically reducing the hardware resource overhead by 98.16% when a 128-bit PUF response is generated. Moreover, the bit per cost (BPC) metric of our proposed RPPUF increased by up to 28.5 and 53.37 times than that of PPUF and the improved butterfly PUF, respectively. This confirms that the proposed RPPUF is ultra-lightweight with a good performance, making it more appropriate and efficient to apply in FPGA-based IoT devices with constrained resources.

  • QoE-Aware Traffic Aggregation Using Preference Logic for Edge Intelligence

    Tang P., Dong Y., Chen Y., Mao S., Halgamuge S.

    IEEE Transactions on Wireless Communications (IEEE)  20 ( 9 ) 6093 - 6106 2021.09

    Research paper (scientific journal), Joint Work, Accepted,  ISSN  15361276

     View Summary

    Traffic flows with different requirements of quality of service (QoS requirements) are aggregated into different QoS classes to provide differentiated services (Diffserv) and better quality of experience (QoE) for users. The existing aggregation approaches/QoS mapping methods are based on quantitative QoS requirements and static QoS classes. However, they are typically qualitative and time-varying at the edge of the beyond fifth generation (B5G) networks. Therefore, the artificial intelligence technology of preference logic is applied in this paper to achieve an intelligent method for edge computing, called the preference logic based aggregation model (PLM), which effectively groups flows with qualitative requirements into dynamic classes. First, PLM uses preferences to describe QoS requirements of flows, and thus can deal with both quantitative and qualitative cases. Next, the potential conflicts in these preferences are eliminated. According to the preferences, traffic flows are finally mapped into dynamic QoS classes by logic reasoning. The experimental results show that PLM presents better performance in terms of QoE satisfaction compared with the existing aggregation methods. Utilizing preference logic to group flows, PLM implements a novel way of edge intelligence to deal with dynamic classes and improves the Diffserv for massive B5G traffic with quantitative and qualitative requirements.

  • A Development Method for Safe Node-RED Systems using Discrete Controller Synthesis

    Yamauchi T., Hirano T., Li J., Kawasaki T., Chen Y., Tsuge A., Okoshi T., Nakazawa J., Yoshioka N., Palaiokrassas G., Litke A., Tei K.

    Proceedings - IEEE Congress on Cybermatics: 2021 IEEE International Conferences on Internet of Things, iThings 2021, IEEE Green Computing and Communications, GreenCom 2021, IEEE Cyber, Physical and Social Computing, CPSCom 2021 and IEEE Smart Data, SmartData 2021 (Proceedings - IEEE Congress on Cybermatics: 2021 IEEE International Conferences on Internet of Things, iThings 2021, IEEE Green Computing and Communications, GreenCom 2021, IEEE Cyber, Physical and Social Computing, CPSCom 2021 and IEEE Smart Data, SmartData 2021)     130 - 137 2021

     View Summary

    We present a controller to Node-RED translator (CNT), a tool for developing Node-RED systems that are safe and easy to update continuously. CNT introduces the discrete controller synthesis to conventional Node- Redsystems to provide a guarantee of flow correctness (safety). Flow correctness, which essentially means that the nodes fire at the timing intended by the designer, is crucial in smart city systems that require frequent application updates with no room for design errors. In this work, we propose a method for developing a Node- Redsystem using CNT along with its accompanying algorithm. We also report the results of experiments that demonstrate the usefulness of the proposed method.

  • A PUF-based Scheme for Identify Trusted Mobile Phone Accessories

    Li L., Huang Z., Chen Y., Du M., Wang Q., Liu J.

    Proceedings - 2020 International Conference on Networking and Network Applications, NaNA 2020    459 - 463 2020.12

    Research paper (international conference proceedings), Joint Work, Accepted,  ISSN  9781728189543

     View Summary

    The rapid diffusion of mobile communication technology and smart phone devices has raised the concerns about the security problems of mobile phone accessories. Despite a few effort has been made in this aspect, there are still some deficiencies such as poor compatibility and limited application scope. This article presents a trusted mobile phone accessory identification scheme. Our method uses physically unclonable function (PUF) as hardware security primitives which are embedded in mobile phone accessories to generate digital signatures, so that they can be applied to identify authorized mobile phone accessories. We finally implement the proposed scheme on a field programmable gate array (FPGA) platform. Experimental results show that our solution can effectively identify trusted mobile phone accessories.

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Reviews, Commentaries, etc. 【 Display / hide

  • 地域を網羅する IoT と情報の力による街のスマート化

    陳 寅, 中澤 仁

    電気学会誌 141 ( 1 ) 11 - 14 2021.01

    Article, review, commentary, editorial, etc. (scientific journal), Joint Work,  ISSN  1340-5551

Research Projects of Competitive Funds, etc. 【 Display / hide

  • Study on an intelligent sensing system for fine-grained data of urban garbage discharge

    2021.04
    -
    2024.03

    MEXT,JSPS, Grant-in-Aid for Scientific Research, Grant-in-Aid for Early-Career Scientists , Research grant, Principal investigator

     View Summary

    ゴミ収集動画を用い、物体検出及び追跡技術による、収集されたゴミ袋の数を自動的に計数する知的なセンシングシステムを開発し、藤沢市のゴミ清掃車に装着し実証実験を行う。細粒度的な都市ゴミのセンシングシステムが世界中の最初の試みとして、本研究は、a)提案されたシステムで精度と処理速度をに評価し、b)収集されたデータの応用性を調査し、c)新しい車両エッジ中心のコンピューティングパラダイムを検証する。

  • Modeling, Design and Implementation of Heterogeneous Opportunistic Urban Sensor Network using Garbage-collecting Trucks as Communication Backbones

    2017.04
    -
    2019.03

    MEXT,JSPS, Grant-in-Aid for Scientific Research, CHEN Yin, Grant-in-Aid for Young Scientists (B), Research grant, Principal investigator

     View Summary

    To implement the vehicular urban sensing technology, we have investigated: (1) Network modeling for the transmission opportunity of mobile network, (2) experiment system using sensors installed on garbage trucks, and (3) applications, like Omimamori service and sensing of garbage disposal, based on the data collected from the experiment system. It is expected that the developed technologies will be applied to fulfill the version of a super smart society.

Intellectual Property Rights, etc. 【 Display / hide

  • 通信装置及びプログラム

    Date applied: 特願2021-087819  2021.05 

    Date issued: 特願2021-087819  2021.05

    Patent, Joint

  • 探索装置、探索方法および 探索プログラム

    Date applied: 特願2021-076602  2021.04 

    Date issued: 特願2021-076602  2021.04

    Patent, Joint

  • 画像処理装置、画像処理方法、および、画像処理プログラム

    Date applied: 特願2020-189851  2020.11 

    Date issued: 特願2020-189851  2020.11

    Patent, Joint

Awards 【 Display / hide

  • WSN-IoT AWARD 2019 最優秀賞

    2019.05, YRP研究開発推進協会 WSN協議会

    Type of Award: Award from publisher, newspaper, foundation, etc.

  • 情報処理学会MBL研究会 第88回研究会 優秀論文

    米澤拓郎,伊藤友隆,陳寅,中澤仁, 2018.08, 情報処理学会MBL研究会, SOXFire: XMPPに基づく都市センサ情報流通基盤

    Type of Award: Award from Japanese society, conference, symposium, etc.

  • デジタルプラクティス論文賞

    中澤仁 陳寅 米澤拓郎 大越匡 徳田英幸, 2018.02, 情報処理学会

    Type of Award: Award from Japanese society, conference, symposium, etc.

 

Courses Taught 【 Display / hide

  • FUNDAMENTALS OF INFORMATION TECHNOLOGY 2

    2020

  • FUNDAMENTALS OF INFORMATION TECHNOLOGY 1

    2020

  • FUNDAMENTALS OF INFORMATION TECHNOLOGY 2

    2019

  • FUNDAMENTALS OF INFORMATION TECHNOLOGY 1

    2019

Courses Previously Taught 【 Display / hide

  • FUNDAMENTALS OF INFORMATION TECHNOLOGY

    Keio University

    2018.04
    -
    2019.03

    Full academic year, Lecture, Lecturer outside of Keio, 26people

Educational Activities and Special Notes 【 Display / hide

  • ミニプロジェクト実装を活用したプログラミング学習促進の取組

    2018.04
    -
    2021

    , Device of Educational Contents

     View Details

    大学一年生を対象とする情報基礎の授業において、ミニプロジェクト実装を活用し、学生のプログラミング学習を促進する取り組みを実践した。

  • 社会連携型の研究会教育の実践

    2014.11
    -
    Present

    , Device of Educational Contents

     View Details

    研究室に履修した学生を積極的に自治体との共同研究に取り込んで、社会問題の解決を目指す研究をさせることで、学生の研究意欲、コミュニケーション力及び社会貢献意識を同時に教育実践を行なった。

 

Memberships in Academic Societies 【 Display / hide

  • Association for Computing Machinery, 

    2018.10
    -
    Present
  • IPSJ, 

    2018.04
    -
    Present
  • IEEE Computer Society, 

    2014.11
    -
    Present

Committee Experiences 【 Display / hide

  • 2020

    Local chair, ACM SenSys2020 Organizing Committee

  • 2020

    Local chair, ACM BuildSys2020 Organizing Committee

  • 2018

    Registration chair, IEEE RTCSA2018 Organizing Committee