A Novel TRNG Based on Traditional ADC Nonlinear Effect and Chaotic Map for IoT Security and Anticollision

In the rapidly developing Internet of Things (IoT) applications, how to achieve rapid identification of massive devices and secure the communication of wireless data based on low cost and low power consumption is the key problem to be solved urgently. This paper proposes a novel true random number generator (TRNG) based on ADC nonlinear effect and chaotic map, which can be implemented by traditional processors with built-in ADCs, such as MCU, DSP, ARM, and FPGA. The processor controls the ADC to sample the changing input signal to obtain the digital signal DADC and then extracts some bits of DADC to generate the true random number (TRN). At the same time, after a delay based on DADC, the next time ADC sampling is carried out, and the cycle continues until the processor stops generating the TRN. Due to the nonlinear effect of ADC, the DADC obtained from each sampling is stochastic, and the changing input signal will sharply change the delay time, thus changing the sampling interval (called random interval sampling). As the input signal changes, DADC with strong randomness is obtained. The whole operation of the TRNG resembles a chaotic map, and this method also eliminates the pseudorandom property of chaotic map by combining the variable input signal (including noise) with the nonlinear effect of ADC. The simulation and actual test data are verified by NIST, and the verification results show that the random numbers generated by the proposed method have strong randomness and can be used to implement TRNG. The proposed TRNG has the advantages of low cost, low power consumption, and strong compatibility, and the rate of generating true random number is more than 1.6 Mbps (determined by ADC sampling rate and processor frequency), which is very suitable for IoT sensor devices for security encryption algorithms and anticollision