Authorization Request Screening for Brute-Force Attack Prevention
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Solution Overview
Problem
Brute-force attacks on networked computer systems consume significant resources, degrade performance, and can lead to denial-of-service for legitimate users by generating high volumes of malicious network traffic, particularly in credit card payment networks where cybercriminals iterate through numerous combinations of account numbers and verification values.
Innovation Solution
Implementing a system with client and bridge platforms that identify and intercept malicious authorization requests in real-time, using velocity thresholds and historical data to determine malicious activity, and adapt security profiles dynamically to prevent such attacks from reaching the bridge platform.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the system allows all authorization requests to pass through to the bridge platform for processing, then legitimate transactions can be processed normally, but the system becomes vulnerable to brute-force attacks that consume excessive resources and degrade performance
Solution Approach 1:
The intermediate client platform performs preliminary analysis of authorization requests before they reach the bridge platform. By examining request patterns, velocity, and characteristics in advance, the system can identify and block malicious brute-force attacks before they consume bridge platform resources, while allowing legitimate requests to pass through unchanged.
Solution Approach 2:
The intermediate client platform acts as an intermediary between the originating client platform and the bridge platform. It intercepts authorization requests, analyzes them for malicious patterns, and selectively forwards only legitimate requests to the bridge platform, thereby protecting the bridge platform from resource exhaustion while maintaining normal transaction processing.
2Reliability
If the system implements real-time analysis of all authorization requests to detect malicious activity, then brute-force attacks can be identified and blocked, but the system consumes additional processing resources and increases latency
Solution Approach 1:
The system applies different levels of analysis to different authorization requests based on their characteristics. Legitimate requests with normal velocity patterns are forwarded with minimal inspection, while requests exhibiting suspicious patterns trigger more intensive analysis. This localized quality approach ensures thorough attack detection only where needed, conserving processing resources.
Solution Approach 2:
The system dynamically adjusts analysis parameters such as velocity thresholds and inspection depth based on observed request patterns. When normal traffic conditions are detected, the system uses lighter inspection modes with lower resource consumption. When anomaly patterns emerge, the system intensifies analysis parameters to improve detection capability, optimizing the balance between security and resource usage.
3Ease of operation
If the system uses high velocity thresholds for identifying malicious requests, then fewer legitimate requests are incorrectly blocked, but malicious brute-force attacks can more easily evade detection
Solution Approach 1:
The velocity threshold is not a fixed value but a dynamic parameter that adapts to changing traffic conditions and attack patterns. The system continuously monitors request velocities and adjusts thresholds in real-time, lowering them when attack patterns are detected and raising them when traffic is normal. This dynamic adjustment maintains high detection accuracy without permanently restricting legitimate transactions.
Solution Approach 2:
The system implements feedback loops where detection results and traffic patterns are continuously analyzed to refine velocity thresholds. When malicious requests are detected, the system learns from these patterns and adjusts thresholds to improve future detection. This feedback mechanism ensures that thresholds remain optimized for both allowing legitimate traffic and blocking attacks.
Data Source
AI summary
A system includes an originating client platform, a first intermediate client platform, and a bridge platform. A first electronic processor of the originating client platform is configured to generate an authorization request and transmit the authorization request. A second electronic processor of the first intermediate client platform is configured to receive the authorization request and determine whether the authorization request is malicious or not malicious. In response to determining that the authorization request is malicious, the second electronic processor is configured to store the authorization request in a data store, transmit an authorization request denial, and transmit an incident payload including details of the authorization request. A third electronic processor of the bridge platform is configured to receive the incident payload, generate a security profile based on the incident payload, and transmit the security profile to a second intermediate client platform.