Identification of vibration sources, defects and/or material properties consists generally in solving inverse problems. The called RIFF method (French acronym meaning Windowed and Filtered Inverse Solving) is one way to solve this kind of inverse problem. The basic principle of the RIFF approach consists in measuring vibration displacement on a meshgrid in a local area of interest, injecting measured data in the motion equation and calculating the searched unknown. Compared to other usual inverse techniques, the RIFF method has the curious particularity of needing the knowledge of the local motion equation only. Boundary conditions, sources or dynamic behaviors outside the area of interest can be completely ignored, whereas they are required for the direct problem solving. The searched unknown can then be identified locally with respect to the frequency and can be mapped by using a scanning process of the area of interest. However, as in all inverse methods, the RIFF approach is very sensitive to uncertainties in measured data, so that it is practically impossible to apply it without a regularization technique. Several approaches based on the use of low-pass wavenumber filtering are presented. Initially developed for vibration source identification, the first examples shown concern location and quantification of point forces and/or moments. A special focus is also proposed on aeroacoustic excitation identification. Since the method corresponds to a local verification of the motion equation, defects can be located. An experimental example on a notch detection is shown on a plate. Finally, the recent development on identification of elastic and damping material properties is presented. Examples showing the possibility to characterize composite materials in medium and high frequency ranges and to realize maps of material characteristics are presented. Actual works and perspectives in industrial applications are discussed at the end of the presentation.