Malicious User Identification via Service Request Analysis
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Solution Overview
Problem
Existing systems fail to effectively identify malicious users in online transactions, particularly in e-commerce, due to inadequate authentication and insecure integration with payment processing services, leading to potential card guessing and validation attacks.
Innovation Solution
A computer-implemented method and system that identifies malicious users by analyzing service requests and responses, using thresholds and fingerprints to flag and block suspicious activity, and dynamically managing security measures to prevent malicious access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If minimal authentication or no authentication is performed for frictionless checkout, then ease of operation is improved, but security is worsened
Solution Approach 1:
The system performs preliminary analysis of service requests by obtaining and analyzing multiple service requests and responses before making a malicious user determination. Fingerprints are extracted from requests in advance, and thresholds are pre-established for identifying suspicious patterns, enabling security checks to be performed proactively rather than reactively.
Solution Approach 2:
The system introduces an intermediary analysis layer between the user and the transaction processing system. This intermediary obtains service requests, analyzes fingerprints and patterns, compares them against thresholds, and determines malicious user status before allowing transactions to proceed, thus maintaining frictionless checkout for legitimate users while blocking malicious ones.
2Reliability
If service requests are analyzed to identify malicious users, then security is improved, but device complexity is worsened
Solution Approach 1:
The system segments the malicious user identification process into distinct functional components: obtaining service requests, extracting fingerprints from requests, analyzing service responses, comparing against thresholds, and determining malicious user status. This segmentation allows each component to be independently implemented and managed, reducing overall system complexity.
Solution Approach 2:
The system enables the processing system to automatically analyze its own service requests and responses without requiring external intervention. The thresholds for identifying malicious users are established within the system itself, and the determination of malicious user status is performed autonomously based on pre-defined criteria, reducing the need for complex external security infrastructure.
3Measurement precision
If multiple service requests are analyzed before identifying malicious users, then measurement precision is improved, but loss of time is worsened
Solution Approach 1:
The system performs preliminary extraction of fingerprints from service requests and pre-establishes thresholds for malicious user identification. By preparing these analytical components in advance, the system can quickly compare incoming requests against pre-defined criteria, reducing the time required for actual malicious user determination while maintaining high detection accuracy through multi-request analysis.
Data Source
AI summary
A method, system, and computer program product for identifying a malicious user obtain a plurality of service requests for a service provided by a processing system, each service request of the plurality of service requests being associated with a requesting user and a requesting system, and a plurality of service responses associated with the plurality of service requests, each service response of the plurality of service responses being associated with the processing system; and identify the requesting user as malicious based on the plurality of service requests and the plurality of service responses.