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The explosive increase in the number of IoT devices requires various types of communication methods. This paper presents secure personal authentication using electrostatic coupling Intra-body communication (IBC) based on frequency shift keying (FSK) and error correction. The proposed architecture uses GPIO for a transmitter and analog-to-digital conversion (ADC) for a receiver. We mplemented FSK modulation, demodulation, data protection, and error correction techniques in the MCU software without applying hardware devices. We used the characteristic that the carrier signal is 50% duty square wave for 1-bit error correction and applied a method of randomly inverting SHA1 hash data to protect user authentication data during transmission. The transmitter modulates binary data using a square wave as a carrier signal and transmits data through the human body. The receiver demodulates the signal using ADC and decrypts the demodulated binary data. To determine the carrier frequency from ADC results, we applied a zero-crossing algorithm which is used to detect edge characteristics in image processing. When calculating the threshold value within the zero-crossing algorithm, we implemented an adaptive threshold setting technique utilizing Otsu’s binarization technique. We found that the size of the electrode pad does not affect the signal strength, but the distance between the electrode pad and the skin has a significant effect on the signal strength. Our results show that binary data modulated with a square wave can be successfully transmitted through the human body, and, when 1-bit error correction is applied, the byte error rate on the receiver side is improved around 3.5% compared to not applying it.

The explosive increase in the number of IoT devices requires various types of communication methods. This paper presents secure personal authentication using electrostatic coupling Intra-body communication (IBC) based on frequency shift keying (FSK) and error correction. The proposed architecture uses GPIO for a transmitter and analog-to-digital conversion (ADC) for a receiver. We mplemented FSK modulation, demodulation, data protection, and error correction techniques in the MCU software without applying hardware devices. We used the characteristic that the carrier signal is 50% duty square wave for 1-bit error correction and applied a method of randomly inverting SHA1 hash data to protect user authentication data during transmission. The transmitter modulates binary data using a square wave as a carrier signal and transmits data through the human body. The receiver demodulates the signal using ADC and decrypts the demodulated binary data. To determine the carrier frequency from ADC results, we applied a zero-crossing algorithm which is used to detect edge characteristics in image processing. When calculating the threshold value within the zero-crossing algorithm, we implemented an adaptive threshold setting technique utilizing Otsu's binarization technique. We found that the size of the electrode pad does not affect the signal strength, but the distance between the electrode pad and the skin has a significant effect on the signal strength. Our results show that binary data modulated with a square wave can be successfully transmitted through the human body, and, when 1-bit error correction is applied, the byte error rate on the receiver side is improved around 3.5% compared to not applying it. [ABSTRACT FROM AUTHOR]