Anonymization Validation for Telecommunication Records
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Solution Overview
Problem
Mobile telecommunication carriers face challenges in ensuring the privacy of subscribers' communication records when sharing aggregated data with third-party servicers, as existing methods may not adequately protect personally identifiable information, potentially compromising subscriber privacy.
Innovation Solution
Implementing a data export engine that generates a communication record table, performs opt-out filtering, network cell anonymity filtering, and telephone number encryption, followed by validation processes to ensure anonymization and protect subscriber privacy, thereby preventing the sharing of personally identifiable information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If aggregated subscriber communication records are shared with third-party servicers to provide additional products or services, then productivity and service capability are improved, but subscriber privacy protection may be compromised
Solution Approach 1:
The patent extracts and removes personally identifiable information (PII) from communication records before sharing aggregated data with third-party servicers. The system identifies and eliminates specific fields such as subscriber IDs, phone numbers, and location data that could directly identify individuals, while retaining aggregated statistical patterns that provide analytical value.
Solution Approach 2:
The patent introduces an intermediary anonymization processing system between the carrier network and third-party servicers. This intermediary layer transforms raw communication records into anonymized aggregated data, acting as a buffer that enables data sharing while protecting subscriber privacy through automated de-identification processes.
2Object-affected harmful factors
If data anonymization is performed to protect subscriber privacy, then privacy protection is improved, but data utility and analysis accuracy may deteriorate
Solution Approach 1:
The patent applies different levels of anonymization to different types of data fields based on their sensitivity and identifiability. Highly sensitive fields like subscriber IDs and phone numbers are completely removed, while less sensitive aggregated statistical fields are retained with minimal modification, preserving data utility while protecting privacy where most critical.
Solution Approach 2:
The patent transforms data parameters by changing the granularity and aggregation level of information. Individual-level records are aggregated into group-level statistics, and specific identifying parameters are replaced with generalized categories, maintaining analytical value while reducing identifiability risks.
3Reliability
If multiple validation checks are implemented to ensure privacy compliance, then reliability of privacy protection is improved, but device complexity and processing time increase
Solution Approach 1:
The patent implements preliminary validation checks during the data anonymization process itself, rather than performing separate post-processing audits. The system validates that PII removal and aggregation meet privacy requirements before data is exported to third parties, preventing non-compliant data from leaving the carrier network in the first place.
Solution Approach 2:
The patent employs automated self-validating anonymization processes that inherently check their own output for compliance. The anonymization system includes built-in verification mechanisms that automatically confirm de-identification effectiveness without requiring external audit systems, reducing overall system complexity while maintaining high reliability.
Data Source
AI summary
The implementation of anonymization validation protects the privacy of subscribers that uses the telecommunication services of a wireless telecommunication network. The anonymization validation checks the data in an anonymized communication record table to ensure the data is properly filtered or encrypted. The anonymized communication record table contains data pertaining to at least one of telephone calls, messages, and data connectivity sessions that are initiated or received by multiple subscribers of a wireless telecommunication network. The anonymized communication record is generated from an original communication record table via filtering out or encryption of the data pertaining to one or more subscribers. The performance of the anonymization validation includes performing opt-out filtering validation, network cell anonymity filtering validation, and telephone number encryption validation on the anonymized communication record table.