Coordinated Privacy Controller for Targeted Communication Campaigns
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing privacy systems for targeted communications fail to adequately protect individual privacy while providing accurate reporting, as they are susceptible to attacks and complications arise in returning a path for source users to serve targeted communications and measure campaign performance.
Innovation Solution
A privacy controller alters datasets in query responses and reports, applying a consistent alteration quantity to maintain individual privacy and ensure accurate reporting, using techniques like differential privacy, k-anonymity, and I-diversity to obfuscate user data and protect against linkage attacks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a privacy system alters datasets to protect individual privacy, then individual privacy is improved, but reporting accuracy deteriorates
Solution Approach 1:
The system changes the parameter of data alteration by applying different alteration quantities to different datasets based on their relationship. The privacy controller identifies that the second dataset (reporting data) is related to the first dataset (query response data) and applies a coordinated alteration quantity to maintain consistency. This resolves the contradiction by transforming the static privacy protection approach into a dynamic, relationship-aware alteration strategy that preserves both privacy and reporting accuracy.
2Reliability
If consistent privacy protocols are applied across multiple datasets, then privacy protection is improved, but system complexity increases
Solution Approach 1:
The privacy controller implements a feedback mechanism by identifying relationships between datasets and using this information to determine coordinated alteration quantities. The system analyzes the connection between the first and second datasets, then applies appropriate alteration strategies accordingly. This feedback loop ensures consistent privacy protection across related datasets while avoiding unnecessary complexity for unrelated data, resolving the contradiction between consistency and complexity.
Data Source
AI summary
Disclosed herein are embodiments providing coordinated privacy for targeted communications and reporting. In particular, the embodiments provide a source user querying an information system to generally identify target users for a communication campaign. A privacy controller alters a first dataset of a query response by a first alteration quantity for transmission to the source user. The source user then generally identifies target users within the first dataset for development of a communication campaign of targeted communications directed to the target users. Subsequently, a reporting system generates a report with a second dataset detailing viewership by target users. The privacy controller alters a second dataset of a report by a second alteration quantity for transmission to the source user. The second alteration quantity is based on the first alteration quantity. Accordingly, for targeted communication campaigns, the privacy controller maintains individual privacy while also providing accurate reporting.