As mshlis begins to touch on, yes we can. However, it will be an unending war. There are quite a few reasons for this. For one, the problem itself is not simple. There are many different 'versions' of the deepfakes framework out in the wild at this point, any algorithm you create to try and spot them would have to work for all of the different iterations. Another reason is the systems that would be used to combat it can be quite easily fooled(see).
However, the most glaring, and unending problem comes from the architecture itself. Let us say we create a perfect algorithm that is foolproof and extremely accurate. Even then, all one would have to do is use that algorithm as the discriminator during training of your deepfakes model, and bing-bang-boom, your deepfake detection model is busted.