Account Authentication Data Analysis for Malicious Network Detection
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Solution Overview
Problem
Network-based content management systems face challenges in preventing the spread of malicious content without burdening themselves with scanning every content item, as they store vast amounts of data, making it impractical to run virus scans on each item.
Innovation Solution
The system identifies malicious user accounts by comparing authentication information and content items, allowing it to block related accounts without scanning every content item, thereby reducing computational resources and time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the content management system runs a virus scan on each content item, then the reliability of detecting malicious content is improved, but the productivity and resource efficiency deteriorate due to the vast quantity of data stored
Solution Approach 1:
The patent extracts and analyzes authentication information (IP addresses, device types, browser types, geographic data) from user accounts separately from the content items themselves. By taking out these identifying features and comparing them across accounts, the system can detect malicious networks without scanning the actual content, thus maintaining detection reliability while improving productivity
Solution Approach 2:
The patent introduces authentication information as an intermediary element to detect malicious content. Instead of directly scanning content items, the system uses authentication data as a mediator to identify related accounts and infer maliciousness, thereby avoiding the computational burden of comprehensive content scanning
2Reliability
If the content management system scans every content item to prevent malicious content spread, then the security against malicious content is improved, but the loss of time and computing resources increases significantly
Solution Approach 1:
The patent performs preliminary analysis of authentication information when user accounts are created or logged in, storing IP addresses, device types, browser types, and geographic data before malicious activity occurs. This preliminary action enables rapid detection of malicious networks without requiring time-consuming content scans when threats are detected
Solution Approach 2:
The system extracts key identifying features from authentication data (IP addresses, device fingerprints, geographic information) and uses these extracted elements for comparison across accounts. This extraction approach allows security detection without investing time and resources into scanning actual content items
3Ease of operation
If the content management system blocks only the identified malicious user account, then the simplicity of the blocking mechanism is maintained, but the reliability of preventing malicious content spread deteriorates because malicious users can create multiple accounts
Solution Approach 1:
The patent implements a feedback mechanism where blocking one malicious account triggers automatic analysis of authentication information from other accounts to identify related malicious accounts. The system uses the detected malicious account's authentication data as feedback to search for and block additional related accounts, thereby maintaining simplicity while improving prevention reliability
Solution Approach 2:
The patent merges the detection and blocking operations into a unified process. When a malicious account is identified, the system simultaneously analyzes authentication information across all accounts using the same IP addresses, device types, and geographic data, then blocks all related accounts in one action, combining multiple functions into a single operational step
Data Source
AI summary
In some embodiments, upon detecting malicious activity associated with a user account, a content management system can identify other user accounts related to the malicious user account. The content management system can identify related user accounts by comparing authentication information collected for the malicious user account with authentication information collected for other user accounts. Authentication information can include IP address information, geographic information, device type, browser type, email addresses, and/or referral information, for example. The content management system can compare the content items associated with the malicious user account to content items associated with other user accounts to determine relatedness or maliciousness. After identifying related malicious user accounts, the content management system can block all related malicious user accounts.