  In image pooled steganalysis, a steganalyst, Eve, aims to detect if a set of
images sent by a steganographer, Alice, to a receiver, Bob, contains a hidden
message. We can reasonably assess that the steganalyst does not know the
strategy used to spread the payload across images. To the best of our
knowledge, in this case, the most appropriate solution for pooled steganalysis
is to use a Single-Image Detector (SID) to estimate/quantify if an image is
cover or stego, and to average the scores obtained on the set of images.
  In such a scenario, where Eve does not know the spreading strategies, we
experimentally show that if Eve can discriminate among few well-known spreading
strategies, she can improve her steganalysis performances compared to a simple
averaging or maximum pooled approach. Our discriminative approach allows
obtaining steganalysis efficiencies comparable to those obtained by a
clairvoyant, Eve, who knows the Alice spreading strategy. Another interesting
observation is that DeLS spreading strategy behaves really better than all the
other spreading strategies.
  Those observations results in the experimentation with six different
spreading strategies made on Jpeg images with J-UNIWARD, a state-of-the-art
Single-Image-Detector, and a discriminative architecture that is invariant to
the individual payload in each image, invariant to the size of the analyzed set
of images, and build on a binary detector (for the pooling) that is able to
deal with various spreading strategies.
