Location-Aware Security Classification for Fake Base Station Detection
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Solution Overview
Problem
In 5G mobile networks, attackers with mobility capabilities can launch fake base station attacks, compromising security and privacy by moving to different locations and intercepting communication content, necessitating effective security analytics across varying geographical areas.
Innovation Solution
A method for obtaining a security classification result involves a security function network element performing security analytics on a target location area based on behavior information of terminal devices, including traffic data and movement tracks, to determine the degree of potential attacks and adjust security protection modes accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If security analytics are performed on all location areas continuously, then security detection capability is improved, but network signaling overhead and processing burden increase
Solution Approach 1:
The patent implements location-area-based security analytics, where different location areas are classified into different security risk levels (high-risk, medium-risk, low-risk). Security analytics are selectively performed based on the specific characteristics of each location area rather than uniformly across all areas. This local differentiation reduces overall signaling overhead while maintaining security detection capability in high-risk areas.
Solution Approach 2:
The patent performs security analytics selectively on specific location areas identified as high-risk or medium-risk, rather than continuously on all location areas. By focusing analytics resources on partial areas where security threats are more likely to occur, the system achieves effective security detection while significantly reducing network signaling overhead and processing burden.
2Reliability
If security protection is forcibly enabled in high-risk areas, then network security is improved, but terminal device power consumption increases
Solution Approach 1:
The patent implements location-area-based security protection policies, where security protection levels are adjusted according to the specific risk characteristics of each location area. In high-risk areas, security protection is forcibly enabled to ensure network security. In low-risk areas, security protection can be relaxed or disabled, thereby reducing terminal device power consumption while maintaining overall network security.
3Measurement precision
If behavior information is collected from all terminal devices, then security analytics accuracy is improved, but privacy protection becomes more difficult
Solution Approach 1:
The patent extracts and analyzes only the necessary behavior information elements required for security assessment, such as terminal device movement patterns, location area changes, and communication behavior characteristics. By selectively extracting only the essential security-relevant information rather than collecting all possible terminal data, the system achieves accurate security analytics while minimizing privacy intrusion.
Data Source
AI summary
Embodiments of this application provide a method for obtaining a security classification result for a location area. A security function network element receives an identifier of a target location area and determines to perform security analytics on the target location area based on the identifier of the target location area. The security function network element may determine a security classification result of the target location area based on first information, where the security classification result indicates a degree to which a potential attack exists in the target location area. The first information is related to behavior information of a terminal device in the target location area, where the behavior information includes traffic data and/or movement track information.