  In recent years, due to the trend in globalization, system integrators have
had to deal with integrated circuit (IC)/intellectual property (IP)
counterfeiting more than ever. These counterfeit hardware issues counterfeit
hardware that have driven the need for more secure chip authentication. High
entropy random numbers from physical sources are a critical component in
authentication and encryption processes within secure systems [6]. Secure
encryption is dependent on sources of truly random numbers for generating keys,
and there is a need for an on chip random number generator to achieve adequate
security. Furthermore, the Internet of Things (IoT) adopts a large number of
these hardware-based security and prevention solutions in order to securely
exchange data in resource efficient manner. In this work, we have developed
several methodologies of hardware-based random functions in order to address
the issues and enhance the security and trust of ICs: a novel DRAM-based
intrinsic Physical Unclonable Function (PUF) [13] for system level security and
authentication along with analysis of the impact of various environmental
conditions, particularly silicon aging; a DRAM remanence based True Random
Number Generation (TRNG) to produce random sequences with a very low overhead;
a DRAM TRNG model using its startup value behavior for creating random bit
streams; an efficient power supply noise based TRNG model for generating an
infinite number of random bits which has been evaluated as a cost effective
technique; architectures and hardware security solutions for the Internet of
Things (IoT) environment. Since IoT devices are heavily resource constrained,
our proposed designs can alleviate the concerns of establishing trustworthy and
security in an efficient and low-cost manner.
