Privacy-Preserving Digital Content Delivery Using Bloom Filters
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Solution Overview
Problem
Existing digital content delivery systems face challenges in efficiently and securely distributing content while preserving user privacy, particularly due to the need to handle sensitive user data without compromising security.
Innovation Solution
A system utilizing probabilistic data structures, such as Bloom filters and cuckoo filters, to encode user membership information, allowing for secure and efficient distribution of digital components by constructing queries directly on these structures without accessing cleartext data, thus maintaining privacy and reducing computational resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If user membership data is stored and processed in cleartext to enable efficient content delivery, then content distribution efficiency is improved, but user privacy and data security are compromised
Solution Approach 1:
The patent introduces probabilistic data structures (Bloom filters, cuckoo filters) as intermediaries between user membership data and content delivery queries. These structures enable the server to perform membership checks without accessing or storing cleartext user data, thus maintaining privacy while enabling efficient content distribution based on user group memberships.
Solution Approach 2:
The patent transforms user membership data from cleartext format into probabilistic data structure format (bit arrays with hashed values). This parameter change allows the system to perform membership queries efficiently while the probabilistic nature of the structure prevents reconstruction of original user data, balancing efficiency and privacy.
2Ease of operation
If traditional data structures are used to store user membership information, then data retrieval is straightforward, but storage requirements and bandwidth consumption increase
Solution Approach 1:
The patent creates a compact probabilistic copy of user membership data that preserves query capabilities while dramatically reducing storage size. Instead of storing complete user profiles and group memberships, the system stores hashed representations in probabilistic structures that occupy minimal space but enable efficient membership verification for content delivery decisions.
Solution Approach 2:
The patent changes the data representation parameters from storing complete user records to storing probabilistic hash-based structures. This transformation reduces the quantity of data stored and transmitted while maintaining the ability to perform membership checks needed for targeted content delivery.
3Measurement precision
If complete user data is accessed to perform membership checks, then accurate content selection is achieved, but computational resources and processing time increase
Solution Approach 1:
The patent extracts only the essential membership verification capability from complete user data. By using probabilistic data structures that store hashed group identifiers, the system performs membership checks without accessing or processing complete user profiles, thereby reducing computational overhead while maintaining sufficient accuracy for content delivery decisions.
Solution Approach 2:
The patent performs preliminary transformation of user membership data into probabilistic structures before content delivery queries are executed. This preliminary action enables fast membership checks during content selection without requiring real-time processing of complete user data, reducing computational resource consumption during the actual content delivery operation.
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for selecting and providing digital contents to a client device are described. The system receives a request including a user membership probabilistic data structure encoding user membership information, and constructs, based on the user membership probabilistic data structure, a query for identifying candidate digital components that are eligible for distribution to users. The system obtains the set of candidate digital components by querying one or more digital component databases using the constructed query, selects, from the candidate digital components, one or more digital components, and provides the one or more digital components to the client device for presentation to the user.