Chaos-Based Physical Unclonable Functions

Security primitives for memoryless IoT devices based on Physical Unclonable Functions and True Random Number Generators

The article describes various security primitives for significantly resource-constrained devices, such as sensors or sensor networks, IoT devices, wearables, etc. - i.e., devices without programmable memory. It is dedicated to parts which cannot handle complex algorithms of modern secure cryptography, cannot be equipped with programmable memories, or their circuits or data in permanent memories can be easily reverse-engineered. Instead, all security techniques (e.g., identification, authentication, and encryption) are based on modern hardware cryptography, mainly: physical unclonable functions (PUFs) and true random number generators (TRNGs). The paper addresses numerous issues from untraceable identification to mutual authentication to one-time pad encryption. The communication security is considered to be a trade-off between the device's resources (processing ability, energy consumption, implementation size, response time), preparation complicity (initialization time, size of a server data storage) and the security capabilities and protection levels. Primitives can be included into the communication protocol based on particular needs and available hardware resources.

Estimation during Design Phases of Suitable SRAM Cells for PUF Applications Using Separatrix and Mismatch Metrics

Physically unclonable functions (PUFs) are used as low-cost cryptographic primitives in device authentication and secret key creation. SRAM-PUFs are well-known as entropy sources; nevertheless, due of non-deterministic noise environment during the power-up process, they are subject to low challenge-response repeatability. The dependability of SRAM-PUFs is usually accomplished by combining complex error correcting codes (ECCs) with fuzzy extractor structures resulting in an increase in power consumption, area, cost, and design complexity. In this study, we established effective metrics on the basis of the separatrix concept and cell mismatch to estimate the percentage of cells that, due to the effect of variability, will tend to the same initial state during power-up. The effects of noise and temperature in cell start-up processes were used to validate the proposed metrics. The presented metrics may be applied at the SRAM-PUF design phases to investigate the impact of different design parameters on the percentage of reliable cells for PUF applications.