• Title/Summary/Keyword: 이미지 센서 DNA

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Trends in Device DNA Technology Trend for Sensor Devices (센서 기반의 디바이스 DNA 기술 동향)

  • Kim, Juhan;Lee, Sangjae;Oh, Mi Kyung;Kang, Yousung
    • Electronics and Telecommunications Trends
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    • v.35 no.1
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    • pp.25-33
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    • 2020
  • Just as it is possible to distinguish people by using physical features, such as fingerprints, irises, veins, and faces, and behavioral features, such as voice, gait, keyboard input pattern, and signatures, the an IoT device includes various features that cannot be replicated. For example, there are differences in the physical structure of the chip, differences in computation time of the devices or circuits, differences in residual data when the SDRAM is turned on and off, and minute differences in sensor sensing results. Because of these differences, Sensor data can be collected and analyzed, based on these differences, to identify features that can classify the sensors and define them as sensor-based device DNA technology. As Similar to the biometrics, such as human fingerprints and irises, can be authenticatedused for authentication, sensor-based device DNA can be used to authenticate sensors and generate cryptographic keys that can be used for security.

DNA (Data, Network, AI) Based Intelligent Information Technology (DNA (Data, Network, AI) 기반 지능형 정보 기술)

  • Youn, Joosang;Han, Youn-Hee
    • KIPS Transactions on Computer and Communication Systems
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    • v.9 no.11
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    • pp.247-249
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    • 2020
  • In the era of the 4th industrial revolution, the demand for convergence between ICT technologies is increasing in various fields. Accordingly, a new term that combines data, network, and artificial intelligence technology, DNA (Data, Network, AI) is in use. and has recently become a hot topic. DNA has various potential technology to be able to develop intelligent application in the real world. Therefore, this paper introduces the reviewed papers on the service image placement mechanism based on the logical fog network, the mobility support scheme based on machine learning for Industrial wireless sensor network, the prediction of the following BCI performance by means of spectral EEG characteristics, the warning classification method based on artificial neural network using topics of source code and natural language processing model for data visualization interaction with chatbot, related on DNA technology.