Harnessing uncertainty in photoresistor sensor for true random number generation in IoT devices

Internet of Things (IoT) has facilitated the connection of many smart devices via internet. Recent cyberattacks have shown that resource constrained IoT nodes are easy prey that lead towards compromising the secrecy of the data and vulnerabilities could be exploited remotely to take control of safety-critical systems. Photoresistor sensors have applications in IoT systems, such as smart street lighting, intelligent cameras, light activated smart consumer electronics, smart home, smart healthcare, etc. Building hardware security primitives, such as True Random Number Generator (TRNG), based on the intrinsic properties of photoresistor would be a novel direction to develop cost-savvy IoT security primitives. Therefore, this paper proposes a TRNG prototype that is devised from uncertainty presents in photoresistor sensors. The proposed TRNG prototype does not require any complex interfacing for preprocessing the weak signal, thereby reducing the unnecessary delay and the recurring hardware cost. The proposed prototype employs the novel approach of additive scrambling that aids to sample sensors at a higher rate. The proposed TRNG has an average random bit generation rate of 8 kbps that is better than the recent work in the literature. The quality of randomness was validated by 15 test batteries of NIST STS test.