Service Request Anonymization With Consistent Sensitive Data Replacement
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Solution Overview
Problem
Conventional data anonymization techniques fail to anonymize sensitive information in service request documents without disrupting the internal structure, making it impossible to share such documents for analysis due to the risk of exposing customer networks to malicious threats and the inability to handle repeated sensitive information accurately.
Innovation Solution
An anonymization server employs a combination of rule-based and deep learning techniques, including data preprocessing, tagging, collision resolution, and replacement logic to identify and identically replace repeated sensitive information, preserving the internal consistency of the documents for meaningful analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If conventional data anonymization techniques are applied to service request documents, then sensitive information is obscured, but the internal structure and consistency of the document are disrupted
Solution Approach 1:
The patent segments the anonymization process into distinct phases: identification of sensitive information, tagging with unique identifiers, and replacement with anonymized tokens. This segmentation allows the system to preserve document structure while removing sensitive data, as each phase operates independently without disrupting the overall document architecture.
Solution Approach 2:
The patent introduces an intermediary tagging system that acts as a mediator between the original sensitive information and the anonymized replacement. Tags serve as temporary placeholders that maintain the document's structural integrity during the anonymization process, allowing the system to replace sensitive data while preserving the original document's internal consistency.
2Productivity
If service request documents are shared for analysis, then technical issue resolution is improved, but customer networks are exposed to malicious threats
Solution Approach 1:
The patent extracts sensitive information from service request documents and replaces it with anonymized tokens. This extraction process removes the harmful elements (sensitive customer network data) while retaining the useful information needed for technical analysis, enabling safe sharing of documents for productivity improvement without exposing customer networks to threats.
Solution Approach 2:
The patent converts the potentially harmful exposure of sensitive information into a benefit by using anonymization tags that preserve document structure and meaning. The same mechanism that could have exposed sensitive data is instead used to protect it while maintaining the document's analytical value, turning a security risk into a security feature that enables safe collaboration.
3Object-affected harmful factors
If repeated sensitive information is anonymized differently, then privacy is enhanced, but internal consistency of the document is lost
Solution Approach 1:
The patent applies a universal tagging approach where the same tag structure and anonymization process is used for all instances of sensitive information, regardless of their specific content or position in the document. This universal method ensures that repeated sensitive information is consistently anonymized, preserving internal document consistency while maintaining privacy protection across all data instances.
Data Source
AI summary
In one example embodiment, a server that is in communication with a network that includes a plurality of network elements obtains, from the network, a service request record that includes sensitive information related to at least one of the plurality of network elements. The server parses the service request record to determine that the service request record includes a sequence of characters that is repeated in the service request record, and tags the sequence of characters as a particular sensitive information type. Based on the tagging, the server identically replaces the sequence of characters so as to preserve an internal consistency of the service request record. After identically replacing the sequence of characters, the server publishes the service request record for analysis without revealing the sequence of characters.