Adaptive Online Identity Reset via Trust-Based Verification
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Solution Overview
Problem
Current online identity and password management systems face challenges in differentiating between legitimate and malicious users during account reset processes, leading to unauthorized access and increased security risks, especially for users who have not implemented two-step verification.
Innovation Solution
The system evaluates user interaction data such as IP address, browser type, account age, and device fingerprint to determine trustworthiness, offering varying levels of reset options based on verified user identity, including full, limited, or no reset options to prevent unauthorized access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional password reset techniques are used, then users can reset their login information, but malicious entities can exploit this to gain unauthorized access to user accounts
Solution Approach 1:
The system applies different verification requirements to different users based on their individual trust scores. Users with high trust scores receive minimal verification, while users with low trust scores undergo more stringent verification processes. This local differentiation resolves the contradiction by making the reset process easy for legitimate users while maintaining strong security for suspicious cases.
Solution Approach 2:
The system dynamically adjusts the reset verification parameters based on the calculated trust score. When trust score exceeds a threshold, the system applies standard reset procedures; when below the threshold, it implements enhanced verification. This parameter-based adaptation allows the system to balance accessibility and security automatically.
2Reliability
If stringent verification requirements are imposed on all users attempting to reset login information, then unauthorized access is prevented, but legitimate users face difficulty resetting their accounts
Solution Approach 1:
Instead of applying uniform verification to all users, the system implements local quality by tailoring verification intensity to each user's trust score. High-trust users experience minimal friction, while low-trust users receive enhanced scrutiny. This resolves the contradiction by making security adaptive rather than universal.
Solution Approach 2:
The verification requirements are made dynamic rather than static. The system continuously evaluates user behavior and updates trust scores, which in turn adjust the verification level. This dynamic approach allows legitimate users to experience easy reset while automatically increasing security for suspicious cases.
3Reliability
If two-step verification is implemented, then unauthorized access is reduced, but user complexity and implementation burden increase
Solution Approach 1:
The system implements dynamic verification where two-step processes are applied selectively based on trust scores rather than universally. Users with high trust scores bypass additional verification, while only low-trust users experience the complexity of enhanced checks. This resolves the contradiction by making complexity conditional rather than inherent.
Solution Approach 2:
The verification complexity is applied locally to specific users based on their trustworthiness assessment. Rather than imposing uniform complexity on all users, the system concentrates verification burden only where needed, resolving the contradiction between security and complexity.
4Ease of operation
If minimal verification is applied to password reset requests, then user experience is improved, but unauthorized access and security risks increase
Solution Approach 1:
The system changes the verification parameter dynamically based on the calculated trust score. For high-trust users, minimal verification is applied to maintain good user experience. For low-trust users, the verification parameter increases to block potential unauthorized access. This resolves the contradiction by making verification intensity adaptive rather than fixed.
Solution Approach 2:
The verification level is customized locally for each user based on their trust score. Legitimate users experience minimal friction, while suspicious cases receive enhanced verification. This local differentiation resolves the contradiction between user experience and security by applying the appropriate level of scrutiny to each case.
Data Source
AI summary
Systems and methods are disclosed for managing the resetting of online identities or accounts of users of Internet web pages. One method includes: receiving, through an electronic device, a request to reset login information to access a web page associated with the user's online account; determining that an IP address associated with the request is not identified as being suspicious; receiving user data intrinsic to the user's request; automatically verifying two or more values of the data intrinsic to the user's request as being indicative of a level of trust of the identity of the user; and transmitting, to the user over the Internet, a subset of options to reset the login information, the subset being selected based on the level of trust.