Adaptive Authentication Using Location and Biometric Risk Scoring
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Solution Overview
Problem
Existing authentication methods for online accounts are insecure due to the ease of forging identification and the availability of personal data, leading to increased instances of hacking and fraud, especially in real-world transactions where multiple forms of verification are needed.
Innovation Solution
Implementing adaptive authentication processes that utilize multiple factors, including location verification through GPS, biometric identification, and secure device interactions like ATM transactions, combined with machine learning algorithms to assess risk scores and create fraud profiles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional single-factor authentication (password or ID) is used, then ease of operation is improved, but reliability of authentication is worsened due to ease of forging identification and availability of personal data
Solution Approach 1:
The authentication process is segmented into multiple independent verification factors: possession factor (device control), knowledge factor (passcode), and biometric factor (liveness detection). Each factor addresses different security dimensions, making the overall system more reliable while maintaining operational ease through adaptive selection of required factors.
Solution Approach 2:
The system performs preliminary actions by continuously monitoring device state, location, and biometric data before completing authentication. Liveness detection and device control verification are performed in advance to prevent fraud, ensuring that the authentication state is genuinely secure before granting access.
2Reliability
If multiple authentication factors are required, then reliability of authentication is improved, but device complexity and operation difficulty increase
Solution Approach 1:
The authentication system dynamically adjusts the number and type of verification factors required based on real-time risk assessment. The adaptive authentication state machine evaluates device control status, location consistency, and biometric liveness to determine whether to require full multi-factor authentication or accept simplified verification, optimizing both security and usability.
Solution Approach 2:
The system performs self-verification by automatically detecting device control status through interaction challenges, determining location consistency without manual input, and verifying biometric liveness through automated sensing. This reduces operational complexity by eliminating manual verification steps while maintaining high reliability through autonomous security checks.
3Reliability
If adaptive authentication with risk assessment is implemented, then reliability of fraud detection is improved, but loss of time increases due to additional verification steps
Solution Approach 1:
The system performs preliminary risk assessment by continuously monitoring device state, location, and user behavior patterns before authentication attempts. This pre-computed risk profile enables the system to quickly determine the appropriate authentication level, reducing time loss by avoiding unnecessary verification steps for low-risk scenarios while maintaining high fraud detection accuracy.
Solution Approach 2:
The authentication system uses feedback loops to continuously refine risk assessment based on authentication outcomes, device responses, and biometric verification results. This adaptive feedback mechanism improves fraud detection accuracy over time while optimizing authentication time by learning from patterns and adjusting verification requirements dynamically.
Data Source
AI summary
Systems and techniques for an system are described herein. In an example, an adaptive authentication system is adapted to receive a request at a first entity from a second entity for secure data of a user, where the second entity is remote from the first entity. The adaptive authentication system may be further adapted to transmit a prompt to a user device associated with the user for authentication of the user and authentication of the request. The adaptive authentication system may be further adapted to receive a response to the prompt and authenticate the user and the request based on the response. The adaptive authentication system may be further adapted to transmit the secure data of the user to the second entity.