RIS Path Integrity Validation Using Time-of-Flight Fingerprints
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Reconfigurable intelligent surfaces in mm-Wave communication systems are vulnerable to physical security breaches, as eavesdroppers can tap into signals, compromising the integrity of wireless communication paths.
Innovation Solution
Integrate a reconfigurable delay detection network with metal-insulator-metal capacitors and a receiving antenna into the reconfigurable intelligent surface to monitor signal strength, using time of flight and AI/ML models to detect anomalies and verify path integrity, thereby identifying potential eavesdropping attempts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If reconfigurable intelligent surfaces are deployed to reflect mm-Wave signals to blocked areas, then wireless coverage is improved, but physical security is compromised due to eavesdropping vulnerabilities
Solution Approach 1:
The system performs preliminary actions by establishing expected time of flight values and signal strength thresholds before actual communication occurs. The base station pre-calculates the time of flight for signals reflecting off the RIS and stores these expected values for later comparison with actual received signals, enabling proactive security validation.
Solution Approach 2:
The system implements feedback mechanisms where the UE measures actual time of flight and signal strength of received signals, then compares these measurements against expected values. When discrepancies are detected indicating potential eavesdropping, the system provides feedback to the base station to trigger security responses such as beam reconfiguration or communication suspension.
2Measurement precision
If time of flight measurement is used to validate signal path integrity, then detection accuracy is improved, but device complexity increases due to additional detection networks
Solution Approach 1:
The RIS elements serve multiple functions: they reflect communication signals to provide coverage extension while simultaneously acting as cooperative targets for time of flight measurement and path validation. This multi-functionality eliminates the need for separate dedicated detection infrastructure, reducing overall system complexity while maintaining high measurement precision.
Solution Approach 2:
The system uses the existing communication signal itself as the measurement probe for time of flight detection. The same signal carrying information also provides the timing reference for security validation, eliminating the need for separate test signals or dedicated measurement channels. The UE performs self-measurement of time of flight without requiring additional external measurement devices.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Ensures the integrity of wireless communication paths by detecting unauthorized access attempts, providing a secure communication link through beam fingerprinting and path validation without significant computational overhead.
Implementation Method 1
a relatively inexpensive metasurface can be installed at various locations to reflect and/or refract higher frequency signals
Implementation Method 2
obtaining current time of flight data representative of a current time of flight associated with a current communication signal
Data Source
AI summary
The technology described herein is directed towards using time of flight data to validate path integrity of a wireless communications path between authorized entities, in which a reconfigurable intelligent surface is part of the signal path between a base station and a user equipment, and using signal strength data for evaluating whether the path is compromised. In one example, an eavesdropping entity can tap into part of the signals to and/or from a base station and user equipment via a reconfigurable intelligent surface. As part of monitoring for an eavesdropper, the path is validated based on the time of flight data, and the measured signal strength is evaluated with respect to the expected signal strength. A drop in the expected signal strength indicates a potential eavesdropper. In one implementation, generative adversarial network models are used in the monitoring of the signal path.