Abstract: Embodiments of the present invention provide for machine learning-based systems and methods for preventing fraud in programmatic advertising. The systems and methods provide for applying a plurality of machine learning models to data associated with a bid request, determining if the bid request is associated with fraudulent activity as a result of the machine learning models, and selectively preventing the bid request from being provided to potential buyers based on the determination.
Abstract: Embodiments of the present invention provide for machine learning-based systems and methods for preventing fraud in programmatic advertising. The systems and methods provide for applying a plurality of machine learning models to data associated with a bid request, determining if the bid request is associated with fraudulent activity as a result of the machine learning models, and selectively preventing the bid request from being provided to potential buyers based on the determination.
Abstract: Embodiments of the present invention provide for machine learning-based systems and methods for preventing fraud in programmatic advertising. The systems and methods provide for applying a plurality of machine learning models to data associated with a bid request, determining if the bid request is associated with fraudulent activity as a result of the machine learning models, and selectively preventing the bid request from being provided to potential buyers based on the determination.
Abstract: Embodiments of the present invention provide for real-time bidding of DOOH advertising units. The systems and methods provide for an API associated with at least one DOOH display, wherein the API is configured to receive a bid request indicating an available advertising unit from the at least one DOOH display, provide the bid request to at least one buyer; and receive a bid response from the at least one buyer, wherein the bid response includes content to be played at the at least one DOOH display.
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