  We study survival time statistics in a noisy sample space reducing (SSR)
process. Our simulations suggest that both the mean and standard deviation
scale as $\sim N/N^{\lambda}$, where $N$ is the system size and $\lambda$ is a
tunable parameter that characterizes the process. The survival time
distribution has the form $\mathcal{P}_{N}(\tau)\sim
N^{-\theta}J(\tau/N^{\theta})$, where $J$ is a universal scaling function and
$\theta = 1-\lambda$. Analytical insight is provided by a conjecture for the
equivalence between the survival time statistics in the noisy SSR process and
the record statistics in a correlated time series modeled as drifted random
walk with Cauchy distributed jumps.
