True Random Number Generator Using Bio-related Signals in Wearable Devices

Yu, Hoyoung; Kim, Young‐Min

doi:10.1109/isocc.2018.8649804

Cited by 3 publications

(1 citation statement)

References 6 publications

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“…A TRNG with high entropy is required to generate random numbers that cannot be predicted. In this study, we use TRNG based on Linear-feedback shift register (LFSR) using bio-signals [11]. Photoplethysmogram (PPG) sensors [12], which are built into most wearable devices, measure values by capturing changes in the arterial perfusion rate of light as the arterial blood flow varies with each heartbeat.…”

Section: True Prime Random Number Generatormentioning

confidence: 99%

New RSA Encryption Mechanism Using One-Time Encryption Keys and Unpredictable Bio-Signal for Wireless Communication Devices

Kim

2020

Electronics

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Applying the data encryption method used in conventional personal computers (PC) to wireless communication devices such as IoT is not trivial. Because IoT equipment is extremely slow in transferring data and has a small hardware area compared with PCs, it is difficult to transfer large data and perform complicated operations. In particular, it is difficult to apply the RSA encryption method to wireless communication devices because it guarantees the stability of data encryption because it is difficult to factor extremely large prime numbers. Furthermore, it has become even more difficult to apply the RSA encryption method to IoT devices as a paper recently published indicated that it enables rapid fractional decomposition when using RSA encryption with a prime number generated through several pseudo-random number generators. To compensate for the disadvantages of RSA encryption, we propose a method that significantly reduces the encryption key using a true prime random number generator (TPRNG), which generates a prime number that cannot be predicted through bio-signals, and a disposable RSA encryption key. TPRNG has been verified by the National Institute of Standards and Technology. The NIST test and an RSA algorithm are implemented through Verilog.

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Section: True Prime Random Number Generatormentioning

confidence: 99%