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Digital images are becoming the most commonly used multimedia data nowadays thanks to the massive manufacturing of cheap acquisition devices coupled with the unprecedented popularity of Online Social Networks. As two sides of a coin, massive use of digital images triggers the development of user-friendly editing tools and intelligent techniques that violate image authenticity. By this respect, digital images are less and less trustable as they are easily modified not only by experts or researchers, but also by unexperienced users. It has been also witnessed that malicious use of images has tremendous impact on human perception as well as system reliability. Those concerns highlight the importance to verify image authenticity. In practice, digital images are created, manipulated, and diffused world-wide via many channels. Simply answering to the question "Is an image authentic?'' appears insufficient. Further steps aiming at understanding the provenance of images with respect to acquisition device or distributed platforms as well as the processing history have to be considered significant. This doctoral study contributes solutions to recover digital image provenance under multiple aspects: i) image acquisition device, ii) social network origin, and iii) source-target disambiguation in image copy-move forgery.