Frequency selective filters are defined according to their frequency domain characterstics. And a lowpass filter is the one whose frequency response magnitude is very small for high frequencies that are rejected and is about unity for low frequencies that are passed, hence the name lowpass.
Looking at the frequency response magnitude of a time-domain Gaussian window reveals the fact that it resembles a lowpass filter charactheristic, though not an ideal brickwall type with a steep transition from passband to stopband, but a mild and smooth one instead.
One application of a lowpass filter is in baseband sampling to prevent aliasing. In such an application the type and quality of the utilized lowpass filter is determined by a number of factors such as the bandwidth of the input signal, its spectral characthersitics, the required sampling rate, target SNR etc. When these conditions are mild. You can use a Gaussian filter to bandlimit the input signal for anti-aliasing purposes. However note that a Gaussian filter in continuous time would generally be replaced by a simpler RC lowpass filter as it would be much simpler to implement.
When you are doing discrete-time sample rate conversion, then a Gaussian filter can be applied in time domain. Or as you said you can try a frequency domain masking and inversion back to time: apparently depicting the effect of a nonrealizable (ideal) brickwall filter on the frequency domain. However note that the results will not be identical to a time domain Gausisan filtering and you shall judge it better by testing, before attempting a full analytical description of the difference in between.