Published Paper Details:

The Internet of Things (IoT) is a fast evolving paradigm where remotely identifiable physical objects form an active network, and are able to operate independently without external control. With these smart devices automatically connecting to each other and exchanging private and sensitive data, the potential for malicious attacks greatly increases. As a result, it is widely accepted that the most challenging aspect of IoT will be to ensure security and privacy. This paper proposes an important cryptographic primitive i.e. transition controlled random number generator, that shares overlapping properties and often have structural similarities with PUFs. The integrity of any secure system depends largely on the proper functioning of these units. True Random numbers are needed for encryption keys, nonces, padding bits and many more applications. Software approaches to generate random numbers, called Pseudo Random Number Generators (PRNG) are widely adopted and are suitable for most applications. However, they are susceptible to attacks as their outputs are deterministic functions of the seed, which carries all its entropy. Therefore, hardware-based mechanism to extract randomness from physical phenomena is required for cryptographic applications. As data privacy is one of the key requirements of IoT framework, it can benefit from high entropy TRNGs generating secure keys.