We seek to derive star formation rates (SFR) and stellar masses (M_star) in distant galaxies and to quantify the main uncertainties affecting their measurement. We explore the impact of the assumptions made in their derivation with standard calibrations or through a fitting process, as well as the impact of the available data, focusing on the role of IR emission originating from dust. We build a sample of galaxies with z>1, all observed from the UV to the IR (rest frame). The data are fitted with the code CIGALE, which is also used to build and analyse a catalogue of mock galaxies. Models with different SFHs are introduced. We define different set of data, with or without a good sampling of the UV range, NIR, and thermal IR data. The impact of these different cases on the determination of M_star and SFR are analysed. Exponentially decreasing models with a redshift formation of the stellar population z ~8 cannot fit the data correctly. The other models fit the data correctly at the price of unrealistically young ages when the age of the single stellar population is taken to be a free parameter. The best fits are obtained with two stellar populations. As long as one measurement of the dust emission continuum is available, SFR are robustly estimated whatever the chosen model is, including standard recipes. M_star measurement is more subject to uncertainty, depending on the chosen model and the presence of NIR data, with an impact on the SFR-M_star scatter plot. Conversely, when thermal IR data from dust emission are missing, the uncertainty on SFR measurements largely exceeds that of stellar mass. Among all physical properties investigated here, the stellar ages are found to be the most difficult to constrain and this uncertainty acts as a second parameter in SFR measurements and as the most important parameter for M_star measurements.
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