Control Plane Fingerprinting for IMEI Spoofing Detection
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Solution Overview
Problem
Existing IMEI management methods in mobile communication networks are vulnerable to spoofing, allowing unauthorized terminals to access networks by modifying their IMEI values, which cannot be effectively detected by mobile communication providers.
Innovation Solution
Construct a fingerprint database for each terminal based on control plane messages and their responses using a decision tree and machine learning, to verify the IMEI and detect unauthorized terminals by comparing extracted fingerprints with the database.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If blacklist-based IMEI management method is used, then terminal identification and access control is simplified, but the system becomes vulnerable to IMEI spoofing and modification attacks
Solution Approach 1:
The patent segments the terminal identification process into multiple independent components: IMEI verification, control plane message analysis, and fingerprint generation. Each component operates independently to verify different aspects of terminal authenticity, making the system more robust against spoofing attacks while maintaining operational simplicity.
Solution Approach 2:
The patent introduces control plane messages as an intermediary element between the terminal and the network for verification. These messages carry fingerprint information that mediates the authentication process, allowing the system to verify terminal authenticity without directly relying on the IMEI alone, thus preventing spoofing attacks.
2Measurement precision
If control plane message analysis and fingerprint generation is implemented, then IMEI verification accuracy and unauthorized terminal detection is improved, but system complexity increases
Solution Approach 1:
The patent performs preliminary actions by pre-generating fingerprints for terminals and storing them in the network before actual authentication occurs. During verification, the system simply compares the received fingerprint against the stored one, significantly reducing real-time processing complexity while maintaining high verification accuracy.
Solution Approach 2:
The patent creates a fingerprint copy of the terminal's control plane message characteristics and stores it in the network. This copy serves as a reference template for future comparisons, allowing rapid verification without repeatedly analyzing the entire control plane message structure, thus reducing system complexity.
3Reliability
If fingerprint database construction using machine learning is implemented, then unauthorized terminal detection capability is enhanced, but processing time and computational resources increase
Solution Approach 1:
The patent applies machine learning algorithms in advance to construct the fingerprint database during off-peak hours. The trained model and generated fingerprints are stored for rapid retrieval during actual verification processes, separating the computationally intensive training phase from the time-sensitive verification phase to minimize processing time delays.
Solution Approach 2:
The patent implements a two-stage verification process: first a quick fingerprint comparison for immediate detection, and only if needed, a more comprehensive machine learning-based analysis. This partial application of heavy computational resources only when necessary balances detection capability with processing time efficiency.
Data Source
AI summary
Disclosed is a method and system for international mobile equipment identity (IMEI) verification and unauthorized terminal detection based on contents of control plane messages exchanged in a process of a terminal that accesses a commercial network in a mobile communication network and the method includes constructing a fingerprint database for each terminal using contents of a control plane message generated in a process of a terminal that accesses a commercial network and a response to the control plane message; and verifying IMEI for an arbitrary terminal that accesses the commercial network using the fingerprint database.