Campaign Measurement Using Cryptographic Non-Identifiers
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Solution Overview
Problem
Existing methods for measuring campaign performance between a campaign promoter and a merchant rely on third-party companies, which pose security risks due to insufficient hashing techniques, potentially revealing sensitive information about consumers and merchants.
Innovation Solution
A computer-implemented method that transforms identifiers into non-identifiers, encrypts them using public and private cryptographic keys, and determines intersections to calculate campaign metrics without exposing actual credit card information, ensuring privacy preservation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If third-party companies use hashing of credit card numbers to measure campaign effectiveness, then campaign performance can be measured, but security and privacy are compromised because hashed credit cards can be reversed by unauthorized parties with access to credit card lists
Solution Approach 1:
The patent introduces an intermediary transformation process that converts credit card numbers into non-identifiers through multiple cryptographic steps. Instead of directly hashing credit cards, the system uses modular exponentiation with public keys to transform identifiers into non-reversible non-identifiers, which are then processed by the third party to measure campaign effectiveness without exposing sensitive information.
Solution Approach 2:
The patent fundamentally changes the parameter representation by transforming credit card numbers (identifiers) into non-identifiers through cryptographic parameter changes. The system applies modular exponentiation with public keys to change the form of the data, making it mathematically impossible to reverse while preserving the ability to perform intersection operations for measurement.
2Measurement precision
If third-party companies access credit card information to assess campaign effectiveness, then performance measurement is enabled, but the risk of information leakage increases both to consumers and to the campaign promoter and merchant
Solution Approach 1:
The patent extracts the identifying information from the credit card numbers before processing. By removing the identifier component and retaining only the transformed non-identifier form, the system enables measurement operations while leaving no usable identifying information that could be leaked or misused by the third party or intercepted during transmission.
Solution Approach 2:
The patent converts the potential harm of data exposure into a benefit by using the cryptographic transformation process. The very act of transforming credit card numbers into non-identifiers, which was initially done to enable measurement, simultaneously provides the security benefit of preventing information leakage. The third party receives data that is useful for measurement but useless for identification or fraud.
3Productivity
If deterministic hashing is applied to credit card numbers for processing, then campaign measurements can be performed, but the hashing technique provides insufficient security because hash translation can be computed and reversed
Solution Approach 1:
The patent replaces the mechanical deterministic hashing system with a cryptographic substitution system based on modular exponentiation and public key infrastructure. Instead of using simple hash functions that can be reversed through computation, the system employs mathematically proven cryptographic transformations that provide security while maintaining processing efficiency through the use of public keys.
Data Source
AI summary
A method of measuring a campaign performance includes transforming identifiers into non-identifiers, and providing the non-identifiers to an external processing party; receiving encrypted non-identifiers comprising the non-identifiers after encryption by the external processing party, other non-identifiers, spending values, and a public cryptographic key, each member of the other non-identifiers being associated with a corresponding member of the spending values; encrypting the non-identifiers to generate other encrypted non-identifiers, and determining an intersection of the encrypted non-identifiers and the other encrypted non-identifiers to generate common encrypted non-identifiers; identifying a subset of the spending values associated with members of the encrypted non-identifiers in the common encrypted non-identifiers; and deriving a total spending value based on the subset of the spending values.


