  We propose a novel framework for crowdsourced images to determine the
likelihood of an image being fake. We use a service-oriented approach to model
and represent crowdsourced images uploaded on social media, as image services.
Trust may, in some circumstances, be determined by using only the
non-functional attributes of an image service, i.e., image metadata. We define
intention of changes as a key parameter to ascertain fake image services. A
novel framework is proposed to estimate the intention of underlying changes
considering change in semantics of an image. Our experiments show high accuracy
using a large real dataset.
