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Silicon photomultipliers (SiPMs) are highly-sensitive photodetectors emerging as the technology of choice for many applications, including large high-energy physics experiments where they often are exposed to high radiation fluences . In recent years, there has been an increasing interest in assessing the performance deterioration of such detectors after the irradiation with proton or neutron, with different fluence levels. In this work, samples of different FBK SiPM technologies, made with different manufacturing technologies, were irradiated at the INFN-LNS facility (Italy) with protons reaching fluences up to about 1 0 14 n e q /cm 2 (1 MeV neutron equivalent) and their performances were characterized in detail after about 30-days room temperature annealing. The results show a significant worsening of the primary noise (dark count rate) of the detectors, which increases with the irradiation fluence, whereas the other performance parameters like the micro-cell gain, the correlated noise probability and the photon detection efficiency do not show significant variations up to 1 0 11 n e q /cm 2 at least. The breakdown voltage estimation after irradiation is another important aspect for a SiPM. In this contribution, we show several methods for its estimation and compare the results. We also introduced new methodologies to characterize the performance of the SiPMs when they present a very high level of noise, such as the estimation of the dark count rate based on the measured reverse current, the estimation of variations in the photon detection efficiency through the measurement of the responsivity, and the measurement of the correlated noise and the gain through the average charge in response to a pulsed light signal. Lastly, we also analyzed the spatial localization of the proton-induced defects inside the device, i.e. the defects that mostly contribute to the increase of the DCR of the device, through the emission microscopy (EMMI) technique. In particular, we analyzed the SiPMs at the single cell level, trying to identify and spatially localize the defects.