Login Attempt Analysis for Credential-Stuffing Detection
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Solution Overview
Problem
Conventional methods for controlling access to interactive computing environments fail to effectively detect and prevent credential-stuffing attacks, which involve automated systems using stolen credentials to gain unauthorized access.
Innovation Solution
A detection system that analyzes log-in attempt data from interactive computing environments to identify credential-stuffing attackers based on success percentages and geographical locations, and restricts access accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional access control methods (username/password) are used, then ease of operation is maintained, but security against credential-stuffing attacks deteriorates
Solution Approach 1:
The system performs preliminary analysis of log-in attempt data before granting access. By calculating success percentages and identifying potential credential-stuffing attacks in advance, the system can prevent unauthorized access while allowing legitimate users to proceed without interruption. This resolves the contradiction by maintaining ease of operation for valid users while improving security through proactive detection.
Solution Approach 2:
The patent introduces an intermediary detection system that sits between the conventional username/password authentication and the actual access grant. This intermediary analyzes attempt patterns, calculates success percentages, and determines whether to block access. It mediates between the simplicity of conventional authentication and the need for advanced security, allowing legitimate logins while blocking credential-stuffing attacks.
2Reliability
If access is restricted based on log-in attempt analysis, then security against credential-stuffing attacks is improved, but ease of operation for legitimate users may deteriorate
Solution Approach 1:
The system applies different levels of access control to different entities based on their specific log-in patterns. Legitimate users with high success percentages experience no restriction and maintain ease of operation, while entities showing credential-stuffing patterns are blocked. This localized application of security measures ensures that security improvements do not adversely affect legitimate users.
Solution Approach 2:
The system dynamically changes access parameters based on detected patterns. By calculating success percentages and comparing them against thresholds, the system adjusts access permissions in real-time. This parameter-based approach allows legitimate users to pass through unchanged while automatically restricting access for potential attackers, thus improving security without impacting legitimate operations.
3Device complexity
If conventional access control is used, then device complexity is low, but ability to detect credential-stuffing attacks deteriorates
Solution Approach 1:
The patent implements a multi-functional system that performs both conventional username/password authentication and advanced anomaly detection using the same infrastructure. The detection system analyzes existing log-in attempt data to calculate success percentages and identify credential-stuffing attacks without requiring separate hardware or complex additional components. This universal approach improves detection capability while maintaining relatively low device complexity.
Data Source
AI summary
A computer-implemented method includes accessing data associated with log-in attempts of an interactive computing environment from attempt logs. The method further includes detecting a success percentage of log-in attempts by an entity. Additionally, the method includes identifying the entity as a credential-stuffing attacker based at least in part on the success percentage of log-in attempts by the entity. Moreover, the method includes restricting access to the interactive computing environment by the entity.