On the Entropy of Oscillator-Based True Random Number Generators under Ionizing Radiation

The effects of ionizing radiation on field-programmable gate arrays (FPGAs) have been investigated in depth during the last decades. The impact of these effects is typically evaluated on implementations which have a deterministic behavior. In this article, two well-known true-random number generators (TRNGs) based on sampling jittery signals have been exposed to a Co-60 radiation source as in the standard tests for space conditions. The effects of the accumulated dose on these TRNGs, an in particular, its repercussion over their randomness quality (e.g., entropy or linear complexity), have been evaluated by using two National Institute of Standards and Technology (NIST) statistical test suites. The obtained results clearly show how the degradation of the statistical properties of these TRNGs increases with the accumulated dose. It is also notable that the deterioration of the TRNG (non-deterministic component) appears before that the degradation of the deterministic elements in the FPGA, which compromises the integrated circuit lifetime.Ministerio de Economía y Competitividad (ESP-2015-68245-C4-1-P)Ministerio de Economía y Competitividad (ESP-2015-68245-C4-4-P)Ministerio de Economía y Empresa (TIN2016-79095-C2-2-R)CAM (S2013/ICE-3095

Random‑telegraph‑noise‑enabled true random number generator for hardware security

The future security of Internet of Things is a key concern in the cyber-security field. One of the key issues is the ability to generate random numbers with strict power and area constrains. “True Random Number Generators” have been presented as a potential solution to this problem but improvements in output bit rate, power consumption, and design complexity must be made. In this work we present a novel and experimentally verified “True Random Number Generator” that uses exclusively conventional CMOS technology as well as offering key improvements over previous designs in complexity, output bitrate, and power consumption. It uses the inherent randomness of telegraph noise in the channel current of a single CMOS transistor as an entropy source. For the first time multilevel and abnormal telegraph noise can be utilised, which greatly reduces device selectivity and offers much greater bitrates. The design is verified using a breadboard and FPGA proof of concept circuit and passes all 15 of the NIST randomness tests without any need for post-processing of the generated bitstream. The design also shows resilience against machine learning attacks performed by the LSTM neural network

Designing, Implementing, and Testing Hardware for Cybersecurity

Cybersecurity is one of the key issues facing the world today. With an ever-increasing number of devices connected across the internet, the need to secure all these different devices against potential attackers is an endless effort. This thesis is focussed on the most promising new developments in the hardware aspect of this battle for security. The first section of the thesis looks at what is the current state of the art when it comes to hardware security primitives, with a focus on random number generators and Physically Unclonable Functions (PUF). The strengths and weakness of the current implementations of these systems are analysed so that the areas which are most in need of improvement can be highlighted. The second major section of this thesis is looking to improve how random numbers are generated, which is essential for many current security systems. True random number generators have been presented as a potential solution to this problem but improvements in output bit rate, power consumption, and design complexity must be made. In this work we present a novel and experimentally verified true random number generator that exclusively uses conventional CMOS technology as well as offering key improvements over previous designs in complexity, output bit rate, and power consumption. It uses the inherent randomness of telegraph noise in the channel current of a single CMOS transistor as an entropy source. For the first time, multi-level and abnormal telegraph noise can be utilised, which greatly reduces device selectivity and offers much greater bit rates. The design is verified using a breadboard and FPGA proof of concept circuit and passes all 15 of the NIST randomness tests without any need for post-processing of the generated bitstream. The design also shows resilience against machine learning attacks performed by an LSTM neural network. The third major section describes the development of a novel PUF concept, which offers a new approach to authentication, allowing low power devices to be included in existing networks without compromising overall security. The new PUF concept introduces time dependence to vastly increase the efficiency of entropy source usage, when compared with a traditional PUF. This new PUF also introduces a probability-based model which greatly reduces the required server memory for Challenge Response Pair (CRP) storage when large numbers of CRPs are used. The concept is verified experimentally on nano-scale CMOS technology as well as through simulation and a proof-of-concept circuit. These combined benefits bring the PUF concept much closer to being a viable solution for widespread cybersecurity applications