Network Traffic Tracking System Identifies Rogue Access Patterns
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Solution Overview
Problem
Organizations face challenges in tracking network traffic data and identifying rogue access patterns within their electronic networks, making it difficult to determine if users are accessing data in an acceptable manner.
Innovation Solution
A system comprising a memory device with computer-readable program code and at least one processing device that receives peer user accounts and data, generates relational mappings, and uses machine learning models to compare access patterns and generate an abnormality score, determining if it meets a predetermined threshold.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If organizations track network traffic data and identify rogue access patterns, then network security is improved, but system complexity increases
Solution Approach 1:
The system segments the network security monitoring function into distinct modules: data collection module, relational mapping generation module, access pattern analysis module, and abnormality detection module. Each module processes specific aspects of network traffic data independently, making the complex security monitoring task manageable and maintainable while improving overall system reliability
Solution Approach 2:
The patent introduces a relational mapping as an intermediary structure that connects user accounts, groups, and access patterns. This intermediary layer simplifies the complexity by providing a standardized framework for comparing access patterns across different users and groups, enabling secure identification of rogue behavior without requiring direct complex analysis of all network traffic
2Measurement precision
If the system generates detailed access patterns and compares historical and current data, then detection precision is improved, but processing time increases
Solution Approach 1:
The system performs preliminary actions by pre-establishing group relationships and historical access patterns before current analysis is needed. The relational mapping is generated in advance, and historical data is processed and stored, so that when current network traffic is analyzed, the comparison can be made efficiently without time-consuming real-time analysis of all historical data
Solution Approach 2:
The system applies local quality by focusing the detailed analysis only on specific aspects of access patterns that are most indicative of rogue behavior, such as access timing, data volume, and pattern deviations. Rather than analyzing every detail of all network traffic, the system concentrates computational resources on the most critical detection parameters, improving precision while reducing processing time
Data Source
AI summary
Systems, computer program products, and methods are described herein for tracking network traffic data and identifying rogue access patterns in an electronic network. The present invention is configured to receive a plurality of peer user accounts; receiving a plurality of peer user data associated with the plurality of peer user accounts; generating a relational mapping based at least on the predetermined group; and generating a plurality of peer historical data access patterns based on the plurality of peer user data over the historical predetermined period. The present invention may further be configured to receive a primary user account; receive a plurality of primary user data; generate a plurality of primary user access patterns; compare the plurality of peer historical data access patterns and the plurality of primary user access patterns to generate an abnormality score; and determine whether the abnormality score meets the abnormality threshold.