Probabilistic Hash Call Recognition System
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Solution Overview
Problem
There is a need for a more optimal method to recognize undesirable calls while ensuring the security of user personal data, as existing methods face challenges in accurately identifying suspicious calls and protecting user data from unauthorized access.
Innovation Solution
The method involves generating a call identifier from a probabilistic hash received from a secure device, analyzing these identifiers to identify suspicious calls, requesting additional data from the secure device, and recognizing the call as undesirable based on the analysis of the received data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If personal data is transmitted to remote servers for call classification, then call recognition accuracy is improved, but data security is worsened
Solution Approach 1:
The patent introduces a probabilistic hash function as an intermediary between the original personal data and the remote classification system. This hash function transforms the data into a form that preserves classification capability while eliminating direct data transmission, thus mediating between accuracy needs and security requirements
Solution Approach 2:
Instead of transmitting the original personal data, the system creates a probabilistic hash copy of the data characteristics. This copy contains sufficient information for call classification but cannot be reversed to obtain the original data, effectively separating classification functionality from data exposure
2Object-affected harmful factors
If probabilistic hash is used for data depersonalization, then data security is improved, but measurement precision is worsened
Solution Approach 1:
The patent changes the parameter representation from direct personal data to probabilistic hash values. This transformation maintains the essential characteristics needed for call classification while altering the data format to ensure security, accepting some precision trade-off that is managed through multiple hash features
3Measurement precision
If more personal data is collected for call analysis, then recognition accuracy is improved, but data loss is worsened
Solution Approach 1:
The patent extracts only the essential characteristics needed for call classification and transforms them into probabilistic hashes. By taking out only the necessary data features rather than transmitting all personal data, the system achieves accurate classification while minimizing data exposure and loss
Data Source
AI summary
Disclosed herein are systems and methods for recognizing undesirable calls on a remote device. In one aspect, an exemplary method comprises, generating, for each call, a call identifier from a probabilistic hash received from a secure device, the probabilistic hash having been computed by the secure device based on a unique call identifier associated with call data collected for the call; analyzing the generated call identifiers to identify at least one of the generated call identifiers as a suspicious call identifier; requesting data, from the secure device associated with the suspicious call identifiers, where the requested data includes at least information about the call associated with the suspicious call identifier; and analyzing data received in response to the request and recognizing suspicious call identifier and the call associated with the suspicious call identifier as undesirable based on the analysis of the data received in response to the request.