Password Risk Evaluator for Identity Authentication
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Solution Overview
Problem
Current identity access management systems are vulnerable to identity fraud methods that exploit password reset policies and linked account vulnerabilities, as they primarily focus on protecting against password guessing and theft, failing to address attacks that leverage account linkage and password reset mechanisms.
Innovation Solution
A password risk evaluator system that assigns a risk score to a password/user ID combination by analyzing previous password patterns and preferences, using machine learning techniques to determine the likelihood of the password being authentic, and employing a password preference model to assess similarity, which can include default models if insufficient user data is available.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional password protection mechanisms are used, then password guessing and theft are prevented, but attacks exploiting password reset policies and account linkage remain vulnerable
Solution Approach 1:
The system segments the authentication process into multiple independent verification stages: initial password verification, behavioral biometric analysis, and risk assessment. Each stage operates independently to evaluate different aspects of authentication legitimacy, preventing attackers from bypassing security through single-point vulnerabilities in password reset mechanisms
Solution Approach 2:
The system introduces behavioral biometric analysis as an intermediary verification layer between the user and the password reset process. This intermediary analyzes typing patterns, device usage behavior, and interaction characteristics to mediate whether a password reset request should be permitted, blocking automated attacks while allowing legitimate users to recover access
2Reliability
If password reset mechanisms are made more secure, then unauthorized access is reduced, but legitimate users may face difficulty recovering forgotten passwords
Solution Approach 1:
The system performs preliminary behavioral biometric analysis during the password reset process to pre-establish a baseline of legitimate user behavior patterns. This preliminary action creates a reference profile that enables rapid risk assessment during actual reset attempts, allowing the system to quickly distinguish between legitimate recovery requests and malicious attacks without requiring extensive verification steps
Solution Approach 2:
The system dynamically changes security parameters based on real-time behavioral analysis results. For high-risk requests exhibiting attack characteristics, the system applies stricter verification parameters and may block the request entirely. For low-risk requests matching legitimate user patterns, the system relaxes parameters to enable smooth password recovery, adapting the security level to the specific risk context
Data Source
AI summary
In an embodiment, a password risk evaluator may receive a request including a user identifier (ID) and a password. The password risk evaluator may retrieve a password preference model associated with the user ID, and may determine a risk score indicating a likelihood that the password is associated with the user ID. For example, the password preference model may be based on previous passwords used by the user, and may identify one or more characteristics, formulas, rules, or other indicia typically employed by the user in creating passwords. If the password supplied in the request matches or is similar to one or more elements of the password preference model, it may be more likely that the password in the request is a password supplied by the user. That is, the risk score may be an authentication of the user, or part of the authentication of the user, in some embodiments.