Homomorphic Encryption for Privacy-Preserving Location Fraud Detection
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Solution Overview
Problem
Conventional fraud detection methods face challenges in processing encrypted data due to complexity and regulatory issues related to storing sensitive information, particularly in online transactions, where raw historical login attempt data is required for risk assessment.
Innovation Solution
A privacy-preserving, location-based authentication service using homomorphic encryption, where users define a private encryption key and location sensitivity, allowing encrypted current and historical location data to be processed for authentication without revealing sensitive information, thereby reducing computational complexity and maintaining data privacy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If raw historical login attempt data is stored and processed for fraud detection, then fraud detection accuracy is improved, but data security and privacy are compromised
Solution Approach 1:
The patent introduces homomorphic encryption as an intermediary mechanism that allows the third-party fraud detection service to process encrypted historical login data without ever decrypting it. The encryption scheme enables computational operations on ciphertexts, producing encrypted results that can be decrypted by the client. This mediator approach maintains data security while enabling accurate fraud detection through risk scoring.
Solution Approach 2:
The patent transforms the data state from plaintext to encrypted form using homomorphic encryption properties. By changing the parameter of data representation from readable text to mathematical ciphertexts that support specific operations, the system enables fraud detection algorithms to work on encrypted data, thereby maintaining both security and功能性.
2Object-affected harmful factors
If data is encrypted before sending to third party service, then data security is improved, but computational complexity increases
Solution Approach 1:
The patent applies homomorphic encryption to the historical login data in advance, before it needs to be used for fraud detection. This preliminary encryption action transforms the data into a form that supports computational operations, eliminating the need for complex real-time encryption/decryption operations during fraud detection queries, thereby reducing operational computational complexity.
3Reliability
If sensitive information is sent to third party in raw form, then fraud detection effectiveness is improved, but regulatory compliance deteriorates
Solution Approach 1:
Homomorphic encryption serves as a regulatory-compliant intermediary that allows the system to send encrypted sensitive information to third-party fraud detection services without violating data protection regulations. The encryption mechanism ensures that the third party cannot access the raw sensitive information, thus maintaining regulatory compliance while still enabling effective fraud detection through encrypted data processing.
Data Source
AI summary
Disclosed herein are techniques for use in fraud detection. In one embodiment, the techniques comprise a method. The method comprises receiving an encrypted current location associated with a user. The method also comprises obtaining an encrypted historical location associated with the user and an encrypted location sensitivity metric that relates to a distance within which locations are considered to be the same. The method further comprises performing an authentication operation based on the encrypted current location, the encrypted historical location and the encrypted location sensitivity metric.