Encrypted Reach And Frequency Computation With Collision Detection

The patent introduces an intermediary encryption layer that allows data to be processed without exposing its contents. Encrypted data structures serve as a mediator between data sources and computation results, enabling accurate frequency and reach calculations while preventing direct access to private information. The encryption acts as a protective barrier that maintains both computational accuracy and data privacy.

The patent creates encrypted copies of data structures that preserve the necessary computational properties without revealing the original data. These encrypted representations allow multiple data sources to contribute to unified computations while each source maintains control over its private information. The encrypted copies enable accurate frequency calculations without exposing the underlying private data.

The patent divides large datasets into encrypted data structures that can be processed in manageable segments. Each data source contributes encrypted representations of its data, which are then combined through homomorphic operations. This segmentation allows accurate reach and frequency computation across large datasets while reducing the computational burden on any single system and minimizing network bandwidth requirements compared to transmitting and processing raw data.

The patent transforms data parameters through encryption and homomorphic operations, changing the representation of data from raw form to encrypted form that preserves mathematical properties. This parameter transformation enables accurate frequency and reach calculations without requiring processing of the full raw datasets, thereby reducing computational resources and network bandwidth requirements while maintaining measurement accuracy.