Hashed String Detection System for Password Security
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Solution Overview
Problem
The insecure sharing of hashed strings poses a significant risk to companies, as hashed strings can become less secure when shared, and unhashing them to verify matching can further compromise security.
Innovation Solution
A detection system utilizing a machine learning trained model to identify potentially hashed information in text data, comparing it to a repository of hashed strings, and generating notifications for matches or partial matches.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If hashed strings are shared for verification purposes, then password security can be maintained without unhashing, but the security of the hashed strings deteriorates when they are shared
Solution Approach 1:
The patent introduces a detection system as an intermediary that monitors communication channels for hashed strings without requiring unhashing or direct access to the original passwords. The system detects hashed strings in emails, chat logs, and other communications, allowing verification of password security without compromising the hashed strings themselves.
Solution Approach 2:
The patent replaces traditional mechanical verification methods (direct comparison of passwords or unhashing operations) with a detection-based system that identifies hashed strings through pattern recognition and machine learning models, eliminating the need for unhashing operations that would compromise security.
2Measurement precision
If hashed strings are unhashed to verify matching, then verification accuracy is improved, but security is compromised
Solution Approach 1:
The detection system serves as an intermediary that performs verification without unhashing. It monitors communications for the presence of hashed strings and compares them against stored hashed versions, maintaining security while achieving accurate verification through the intermediary detection layer.
Solution Approach 2:
The system works with copies of hashed strings rather than the original passwords. By detecting and comparing hashed string patterns in communications against a repository of known hashed strings, the system achieves verification accuracy without needing to unhash or expose the original credentials.
3Reliability
If a detection system is implemented to monitor hashed strings, then security monitoring is improved, but device complexity increases
Solution Approach 1:
The detection system is designed to operate autonomously by monitoring communication channels for hashed string patterns without requiring manual intervention. The machine learning models automatically identify and flag potential security issues, reducing the need for complex manual analysis while maintaining effective security monitoring.
Solution Approach 2:
The system uses machine learning models that can adapt to different hashing algorithms and patterns by training on various data types. This allows the detection system to handle multiple security scenarios without requiring complex manual configuration for each specific case, simplifying deployment while maintaining comprehensive monitoring capability.
Data Source
AI summary
Systems and methods may generally be used to identify a hashed password. An example method may include determining, using a machine learning trained model, that text data includes potentially hashed information, and in response, comparing the string to a data set of hashed strings. The method may include determining, from the comparison, that the string corresponds to a stored hashed string of the data set, and in response outputting an indication that the stored hashed string is in the text data.