In this article, we define noiseless privacy, as a non-stochastic rival to differential requiring that the outputs of mechanism (i.e., function composition privacy-preserving mapping and query) attain only few values while varying data an individual (the logarithm number distinct is bounded by privacy budget). Therefore, output not fully informative individuals in dataset. We prove several guar...