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A lightweight true random number generator using beta radiation for IoT applications
Park, Kyunghwan,Park, Seongmo,Choi, Byoung Gun,Kang, Taewook,Kim, Jongbum,Kim, Young-Hee,Jin, Hong-Zhou Electronics and Telecommunications Research Instit 2020 ETRI Journal Vol.42 No.6
This paper presents a lightweight true random number generator (TRNG) using beta radiation that is useful for Internet of Things (IoT) security. In general, a random number generator (RNG) is required for all secure communication devices because random numbers are needed to generate encryption keys. Most RNGs are computer algorithms and use physical noise as their seed. However, it is difficult to obtain physical noise in small IoT devices. Since IoT security functions are required in almost all countries, IoT devices must be equipped with security algorithms that can pass the cryptographic module validation programs of each country. In this regard, it is very cumbersome to embed security algorithms, random number generation algorithms, and even physical noise sources in small IoT devices. Therefore, this paper introduces a lightweight TRNG comprising a thin-film beta-radiation source and integrated circuits (ICs). Although the ICs are currently being designed, the IC design was functionally verified at the board level. Our random numbers are output from a verification board and tested according to National Institute of Standards and Technology standards.
Efficient hardware implementation and analysis of true random-number generator based on beta source
Park, Seongmo,Choi, Byoung Gun,Kang, Taewook,Park, Kyunghwan,Kwon, Youngsu,Kim, Jongbum Electronics and Telecommunications Research Instit 2020 ETRI Journal Vol.42 No.4
This paper presents an efficient hardware random-number generator based on a beta source. The proposed generator counts the values of "0" and "1" and provides a method to distinguish between pseudo-random and true random numbers by comparing them using simple cumulative operations. The random-number generator produces labeled data indicating whether the count value is a pseudo- or true random number according to its bit value based on the generated labeling data. The proposed method is verified using a system based on Verilog RTL coding and LabVIEW for hardware implementation. The generated random numbers were tested according to the NIST SP 800-22 and SP 800-90B standards, and they satisfied the test items specified in the standard. Furthermore, the hardware is efficient and can be used for security, artificial intelligence, and Internet of Things applications in real time.
An Approach for Reducing Computational Time for Real-Time Autonomous Vehicle Tracking
TaeWook Hwang,Seonhee Kim,Sujeong Kim,Gilsang Jang,Jihye Park,Seongha Park,Eric T. Matson,Kyungsup Kim 제어로봇시스템학회 2018 제어로봇시스템학회 국제학술대회 논문집 Vol.2018 No.10
Autonomous vehicles are familiar to public in daily life nowadays. For a recreational purpose, autonomous vehicles such as drones are commonly adopted for people. However with the easy accessibility, those autonomous vehicles can be a threat to anyone. Moreover, to detect and prevent those possible threats, real-time detection and tracking system is required. With the requirements, we propose a real-time communication between post-processing device and autonomous vehicle tracking sensor, which is a radar and a noise reduction method for post-processing. With the proposed method, a Frequency Modulated Continuous Wave (FMCW) radar can be utilized for real-time monitoring of autonomous vehicle. In this paper, we used an audio file recorded through a FMCW radar for distance tracking. The recorded audio data were processed by Inverse Fast Fourier Transformation (IFFT) and noise cancellation. We propose a data selection formula for faster IFFT processing and a noise reduction method in real-time communication. Also we propose a simple Android application to receive the processed data that sent to as distances of the target autonomous vehicle in time in real-time, so that a user can conveniently watch an autonomous vehicle near the radar.