Digital visual media represent nowadays one of the principal means for communication. Lately, the reliability of digital visual information has been questioned, due to the ease in counterfeiting both its origin and content. Digital image forensics is a brand new research field which aims at validating the authenticity of images by recovering information about their history. Two main problems are addressed: the identification of the imaging device that captured the image, and the detection of traces of forgeries. Nowadays, thanks to the promising results attained by early studies and to the always growing number of applications, digital image forensics represents an appealing investigation domain for many researchers. This survey is designed for scholars and IT professionals approaching this field, reviewing existing tools and providing a view on the past, the present and the future of digital image forensics.

In this paper, we propose a new version of FP-Growth algorithm to find association rules. In this version, we vary the minsup value from one level to another. This variation is made in two cases: increasing and decreasing the minsup value. We performed a set of experiments to validate the usefulness of our proposition in the generation of association rules process.

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