Multi-Factor Authorization for Data Interactions
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Solution Overview
Problem
Current multi-factor authentication systems lack robustness in protecting sensitive data interactions from unauthorized access, particularly when initial authentication credentials are compromised, and do not provide customizable security measures tailored to specific data interactions.
Innovation Solution
A central server implements multi-factor authorization by requiring users to provide multiple evidence factors for sensitive data interactions, with user-configured rules triggering additional authorization based on predefined conditions, such as data transfer thresholds, and sends notifications for suspicious activities, enhancing security without necessitating additional authorization for all interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multi-factor authentication is implemented for all data interactions, then security against unauthorized access is improved, but system complexity and user burden increase
Solution Approach 1:
The patent applies local quality by implementing multi-factor authentication selectively for specific high-risk data interactions (e.g., data deletion, large data transfers) rather than uniformly for all interactions. The system analyzes the nature and sensitivity of each data interaction request and triggers additional authentication factors only when necessary, based on pre-defined risk criteria and user-configurable policies.
Solution Approach 2:
The patent implements dynamics by making the authentication requirement adaptive and conditional. The system dynamically determines whether multi-factor authentication is needed based on real-time assessment of interaction characteristics, user behavior patterns, and configured security policies. This allows the authentication mechanism to be flexible rather than static, adjusting security levels according to actual risk.
2Reliability
If additional authorization is required for sensitive data interactions, then data protection is improved, but processing time and operational efficiency worsen
Solution Approach 1:
The patent applies preliminary action by pre-configuring security policies, risk thresholds, and authentication requirements before data interactions occur. Users can pre-define which types of interactions trigger additional authorization and what authentication factors should be required. This preparation work is done in advance, allowing the system to quickly evaluate and process interactions without real-time decision complexity.
Solution Approach 2:
The system applies local quality by providing granular control over authorization requirements for different data interactions. Users can specify exactly which interactions (e.g., deletion, transfer, modification) require additional authentication factors, rather than applying uniform restrictions to all operations. This targeted approach minimizes impact on routine operations while maintaining strong protection for sensitive actions.
3Adaptability or versatility
If user-configurable rules are implemented for triggering additional authorization, then adaptability to specific needs is improved, but system complexity increases
Solution Approach 1:
The patent implements self-service by enabling users to independently configure their own security policies and authorization rules without requiring system administrator intervention. Users can define which data interactions trigger additional authentication, select appropriate authentication factors, and adjust security thresholds according to their specific needs. This empowers users to manage their own security requirements while reducing the burden on system administrators.
Solution Approach 2:
The system applies universality by designing a flexible rule-engine framework that can handle multiple types of authentication factors (password, biometrics, tokens), various data interaction types, and different user roles through a single unified configuration system. This multi-functional architecture allows the same system to adapt to diverse security requirements without requiring separate customization mechanisms for each scenario.
4Measurement precision
If notifications are sent for suspicious activities, then detection capability is improved, but communication overhead and system complexity worsen
Solution Approach 1:
The patent implements feedback by establishing a notification system that provides real-time alerts to users when suspicious or unauthorized data interactions are detected. The system monitors data interactions, compares them against configured security policies and user behavior patterns, and sends notifications (via email, SMS, or in-app alerts) when anomalies are detected. This closed-loop feedback mechanism enables users to respond to potential security incidents promptly.
Solution Approach 2:
The system applies the intermediary principle by introducing a notification service as a mediator between the data interaction monitoring system and the user. Rather than requiring direct complex integration between security monitoring and user alerting mechanisms, the notification service acts as an intermediary layer that standardizes the alerting process and handles various communication channels, thereby simplifying the overall system architecture.
Data Source
AI summary
A system includes a central server and one or more user devices connected by a network. The central server receives a request initiated by a user using a user device for a data interaction associated with a data file. The central server checks whether the user is authorized to perform the requested data interaction based on a list of user authorizations. If the user is authorized to perform the data interaction, the central server checks whether the data interaction satisfies at least one rule defined for the user relating to a type of the requested data interaction. If the data interaction satisfies the at least one rule, the central server performs an additional level of authorization to verify an identity of the user. The central server further processes the data interaction when the additional level of authorization is successful.