Social Media Account Compromise Detection via Affinity Group Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for detecting compromised social media accounts, such as historical analysis and content analysis, often result in false positives and false negatives, failing to accurately identify hacked accounts that distribute malicious content.
Innovation Solution
A system and method that analyzes affinity groups by gathering social media content from multiple platforms, identifying peer groups based on shared attributes, and correlating new posts with historical posts to determine if an account is compromised, providing notifications for potentially compromised accounts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If historical analysis or content analysis is used to detect compromised accounts, then detection capability is provided, but false positives and false negatives increase
Solution Approach 1:
The patent combines multiple detection approaches (historical analysis, content analysis, and affinity group analysis) into a unified detection system. By merging these different analysis methods, the system achieves more reliable detection of compromised accounts while reducing false positives and false negatives that occur when using individual methods alone.
Solution Approach 2:
The patent introduces affinity groups as an intermediary layer between individual account analysis and compromised account detection. By analyzing accounts within their affinity groups and comparing behavior patterns across groups, the system improves detection precision without sacrificing reliability.
2Measurement precision
If traditional detection methods are used, then detection process is simple, but detection accuracy decreases
Solution Approach 1:
The patent segments the detection process into distinct modules: historical analysis module, content analysis module, and affinity group analysis module. Each module performs a specific function, and their results are integrated to achieve high detection accuracy. This segmentation manages complexity by organizing the system into manageable, specialized components.
Solution Approach 2:
The patent adds a new dimension to account detection by incorporating affinity group relationships. Instead of analyzing accounts in isolation or based solely on historical/content data, the system analyzes accounts within the contextual dimension of their affinity groups, improving precision without excessive complexity increase.
3Measurement precision
If affinity group analysis is implemented, then false identifications are minimized, but computational complexity increases
Solution Approach 1:
The patent performs preliminary actions by pre-establishing affinity groups and their characteristics before detection occurs. Affinity groups are formed based on account relationships, and baseline behavior patterns are established in advance. During detection, the system compares observed behavior against these pre-established patterns, improving precision while managing computational complexity through advance preparation.
Data Source
AI summary
Devices and methods for detecting a compromised social media account are disclosed. A method includes: receiving, by a computing device, social media content corresponding to a plurality of social media accounts; determining, by the computing device, a plurality of affinity groups, each including two or more social media accounts from the plurality of social media accounts, based upon the received social media content; determining, by the computing device, whether or not a particular social media account of the plurality of social media accounts is compromised using the received social media content and the determined plurality of affinity groups; and in response to determining that the particular social media account is compromised, the computing device providing a notification indicating that the particular social media account is compromised.