Ad Notice Metadata Analysis for Consumer Privacy Protection

The patent introduces an intermediary system that sits between consumers and ad networks, allowing consumers to control what information is shared. The system uses trusted intermediaries (such as privacy-preserving ad networks) that can perform targeted advertising functions while maintaining consumer privacy through techniques like differential privacy and federated learning, thus resolving the contradiction between targeting precision and privacy protection

The patent changes the parameters of information sharing by introducing granular control mechanisms where consumers can select specific parameters (types of data, duration, purposes) for sharing. This transforms the all-or-nothing privacy model into a configurable model, allowing consumers to maintain privacy while enabling targeted advertising under controlled conditions

The patent implements feedback mechanisms where consumers receive real-time notifications about data collection activities, ad targeting decisions, and privacy policy changes. The system provides continuous feedback loops that allow consumers to monitor and control their privacy settings, thereby enhancing both transparency and reliability of compliance through observable and verifiable processes

The patent requires preliminary actions such as obtaining explicit consumer consent before data collection, pre-notifying consumers about privacy policies, and establishing privacy-by-default settings before any advertising activity begins. These preliminary measures ensure compliance is built into the system architecture rather than added later, improving both transparency and enforcement reliability