Secure Storage for Identification; Random Resources and Privacy Leakage

A Crystallization Robot for Generating True Random Numbers Based on Stochastic Chemical Processes

“…Random numbers are used extensively in many applications, such as cryptography 7 and scientific modeling, 8 where their non-deterministic properties and unpredictability are essential. The source of randomness (i.e., the entropy source) is a crucial factor for whether correlations between generated numbers are present, and this has a great impact on the randomness and utility of the output.…”

Secure Identification for Gaussian Channels and Identification for Multi-Antenna Gaussian Channels

“…Burnashev [10] has shown that for the white Gaussian channel without bandwidth constraint and finite Shannon capacity, the corresponding identification capacity is infinite. Secure identification for discrete alphabets has been extensively studied [6], [11], [12] over the recent decades due to its important potential use in many future scenarios. Indeed, for discrete channels, it was proved in [11] that secure identification is robust under channel uncertainty and against jamming attacks.…”