Signal Injection Detection for Capture-Effect Network Integrity
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Solution Overview
Problem
Wireless and wired communication networks are vulnerable to overshadow and undershadow attacks, where a stronger interfering signal overrides the original signal, compromising communication or sensing capabilities and integrity.
Innovation Solution
An apparatus and system that identify signal element magnitude variations and apply permutation operations to detect and correct signal injections, using AI/ML models and integrity checks to enhance signal integrity by identifying and mitigating overshadow and undershadow attacks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a receiver receives a combination of original signal and stronger interfering signal, then the receiver can demodulate or decode a signal, but the captured signal is distorted and contains only the interfering signal due to the capture effect
Solution Approach 1:
The patent applies preliminary action by performing a permutation operation on the signal elements before transmission. This pre-processing step rearranges the signal elements in a specific order that is known to both transmitter and receiver. When an injection attack occurs, the permutation allows the receiver to detect anomalies by comparing the received permuted signal against the expected permuted sequence, enabling early detection before demodulation/decoding occurs.
Solution Approach 2:
The patent implements feedback by using the known permutation operation as a reference to verify signal integrity. The receiver applies the same permutation operation to the received signal and checks whether the result matches the expected original signal structure. This feedback mechanism allows the system to detect and identify injection attacks by recognizing deviations from the expected permuted pattern.
2Object-affected harmful factors
If an attacker injects a stronger interfering signal to override the original signal, then the attack can compromise communication capabilities, but the injection can be detected through signal element magnitude variation analysis
Solution Approach 1:
The patent replaces traditional signal analysis methods with a permutation-based detection mechanism. Instead of relying solely on magnitude comparison or spectral analysis, the system uses a deterministic permutation operation to transform the signal and enable structural verification. This substitution allows for more robust detection of injection attacks by checking the structural integrity of the permuted signal rather than just its physical characteristics.
3Reliability
If a permutation operation is applied to the signal upon transmission and inverted upon reception, then the integrity of signals can be increased, but the device complexity increases due to additional processing steps
Solution Approach 1:
The patent applies parameter changes by modifying the order of signal elements through a permutation operation. This transformation changes the temporal or spatial arrangement of signal elements without altering their fundamental properties. The permutation serves as an additional parameter layer that enables integrity verification while maintaining compatibility with existing signal processing pipelines through systematic reordering and inversion operations.
Data Source
AI summary
The invention relates to an apparatus (Rx) for increasing an integrity of signals (S) in a signaling network, each signal comprising a sequence of one or more signal elements. The apparatus comprises an identification unit configured to identify any injection (I) of signal elements into a received signal based on at least one of a) a signal element magnitude variation, b) an inversion of a permutation operation applied to the received signal upon transmission, c) a signal fingerprint, d) a location of the transmitter, and e) an AI/ML, Artificial Intelligence/Machine Learning, model. This allows for a reliable identification of injections of signal elements that are due to the capture effect. In particular, not only overshadow attacks, but also undershadow attacks or other injection attacks can be identified. By processing the received signals based on any identified injections of signal elements, the integrity of signals in the network can be increased.