Host Device Connection Fraud Detection With Pre-Connection Scoring
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Solution Overview
Problem
Detecting and preventing fraudulent computing devices in information technology infrastructure is challenging due to the large number of devices, their remote locations, and various types, making active monitoring and management inefficient.
Innovation Solution
A control system that uses a processor and memory to detect fraudulent devices by analyzing connection data, generating a score based on account values, and terminating connections that exceed a fraud threshold, thereby preventing harm to receiver computing devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If active monitoring and management of devices is performed, then fraudulent devices can be detected, but the complexity and resource consumption increase due to the large number of devices
Solution Approach 1:
A control system is introduced as an intermediary component between devices and the monitoring infrastructure. This control system consolidates monitoring functions, allowing fraudulent device detection without requiring complex individual monitoring of each device. The control system acts as a mediator that simplifies the overall monitoring architecture while maintaining detection capabilities.
Solution Approach 2:
The control system performs multiple functions including device monitoring, fraud detection, and connection management within a single unified platform. This multi-functional approach reduces the need for separate specialized systems for each monitoring task, thereby reducing overall system complexity while maintaining comprehensive fraud detection capability.
2Measurement precision
If comprehensive connection analysis is performed to detect fraud, then detection accuracy improves, but processing time increases
Solution Approach 1:
The system performs preliminary fraud risk assessment by analyzing connection data and generating fraud scores before fully establishing connections. Account values and connection patterns are pre-evaluated to identify high-risk connections early in the connection lifecycle, allowing accurate fraud detection without requiring time-consuming analysis of every connection detail.
Solution Approach 2:
The system transforms connection data into fraud scores using configurable thresholds and weighting parameters. By adjusting these parameters, the system can optimize the balance between detection accuracy and processing speed, allowing comprehensive analysis when accuracy is prioritized and faster processing when speed is more critical.
3Object-affected harmful factors
If connections are terminated based on fraud scores, then security against fraudulent devices improves, but false positives may increase
Solution Approach 1:
The system applies preliminary countermeasures by terminating connections that exceed fraud thresholds before fraudulent devices can cause harm. This preventive approach blocks potential fraud attempts early in the connection process, protecting the network from harmful activities while maintaining security.
Solution Approach 2:
The system uses fraud scores as feedback to dynamically adjust connection management decisions. By continuously monitoring connection patterns and updating fraud assessments, the system can distinguish between legitimate and fraudulent connections more accurately, reducing false positives while maintaining protection against actual threats.
Data Source
AI summary
Systems and methods of managing fraudulent devices are provided. The system detects a request for a connection to communicatively couple a technician computing device with a receiver computing device. The system identifies connection data for the connection. The system requests, based on the connection data, a plurality of account values. Each of the plurality of account values is associated with an account that the technician computing device used to establish the connection. The system generates a score indicating a fraudulent level of the account based on the plurality of account values. The system terminates, responsive to a comparison of the score with a fraud threshold, the connection. The system transmits, to a ticketing system, a support ticket generated responsive to the comparison of the score with the fraud threshold.