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Cross-Media Authentication and Verification
Abstract
The present chapter outlines the potentials of cross-media authentication solutions by correlating all the available information streams involved in multiple media (i.e., content/channel-adapted modalities, linking mechanisms, users' feedback, metadata). The proposed model attempts to thoroughly analyze the existed (and detected) diversities, aiming at seeking for “consistent inconsistencies” (i.e., specific dissimilarities that are proportionately steady in most “comparison pairs”). Full range of forgery detection strategies are taken into consideration (i.e., best practices adopted by humans, algorithms, and intelligent systems implemented through machine learning, their dynamic combination, etc.). Thus, the current framework ventures to concatenate all the involved approaches, which are related to both multiple publishing channels and news verification. Hence, the “cross-media” term has a broader meaning, encapsulating the sub-cases of cross-/trans-media publishing and storytelling, with respect to cross-validation of information, along with the entire landscape of digital media.
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