Canary Numbers: Design for Light-weight Online Testability of True Random Number Generators

Vladimir Rozic, Bohan Yang, Nele Mentens, Ingrid Verbauwhede

Abstract: We introduce the concept of canary numbers, to be used in health tests for true random number generators. Health tests are essential components of true random number generators because they are used to detect defects and failures of the entropy source. These tests need to be lightweight, low-latency and highly reliable. The proposed solution uses canary numbers which are an extra output of the entropy source of lower quality. This enables an early-warning attack detection before the output of the generator is compromised. We illustrate the idea with 2 case studies of true random number generators implemented on a Xilinx Spartan-6 FPGA.