Determining Intent of Changes to Ascertain Fake Crowdsourced Image Services

TL;DR

A novel framework is proposed to estimate the intention of underlying changes considering change in semantics of an image to determine the likelihood of an image being fake.

Abstract

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.

Figures (14)

• Figure 1: Motivating Scenario
• Figure 2: Categorization of Potential Modifications in an Image
• Figure 3: Possible Extrinsic Changes in Images
• Figure 4: Possible Intrinsic Changes in Images
• Figure 5: Proposed System Model