Distributed RF Anomaly Detection via Edge Sensor Correlation
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Solution Overview
Problem
Existing systems for detecting compromised communication networks face challenges with high computational demands and bottlenecks as the number of devices increases, leading to errors, slow processing, and failures, even with high-powered processors.
Innovation Solution
A distributed correlation system that uses a multi-tier approach with sensor devices and a service layer, where sensor devices extract and correlate RF signal data with local databases to detect anomalies, and transmit enriched information to the service layer for further analysis and user alerts, offloading computational load from central processors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a centralized server processes and analyzes data from a large number of devices, then detection capability is improved, but processing speed and reliability deteriorate due to computational bottlenecks
Solution Approach 1:
The patent divides the centralized processing architecture into distributed edge computing nodes deployed across multiple devices. Each edge node performs local anomaly detection on its own data, segmenting the overall processing task to eliminate the single-point bottleneck and enable parallel processing across the network.
Solution Approach 2:
The patent introduces a hierarchical architecture where edge computing nodes serve as intermediaries between local devices and the central server. These intermediaries perform preliminary processing and filtering, reducing the data volume that must be transmitted and processed centrally while maintaining detection accuracy.
2Measurement precision
If a centralized server processes data from a large number of devices, then comprehensive analysis is improved, but system reliability deteriorates due to processing errors and failures
Solution Approach 1:
The patent segments the processing function across multiple independent edge nodes rather than relying on a single centralized server. This distribution eliminates single-point failures, as each node operates independently and can continue functioning even if other nodes or the central server experience failures.
Solution Approach 2:
The patent implements local anomaly detection capabilities at edge nodes before data reaches the central server. This preliminary detection layer acts as a cushion, filtering out obvious anomalies locally and reducing the burden on central processing, thereby preventing system overload and failures.
3Measurement precision
If computational processing is performed centrally, then analysis capability is improved, but energy consumption and computational burden on the central system increase
Solution Approach 1:
The patent segments computational tasks between edge nodes and the central server based on processing requirements. Simple anomaly detection is performed locally at edge nodes with minimal energy consumption, while only aggregated results and complex patterns are processed centrally, distributing the energy burden efficiently.
Solution Approach 2:
The patent implements partial processing at the edge level, where only the necessary minimum computation for local anomaly detection is performed. This avoids excessive central processing by handling routine detection tasks locally, reducing overall computational energy consumption while maintaining detection effectiveness.
Data Source
AI summary
An apparatus for distributed correlation of RF information includes a radio having an RF transceiver and sensor in communication with the radio. The sensor has a collector for extracting signal data from the radio and a correlator for correlating the extracted signal data with sensor correlation data stored within a database within the sensor to detect an anomaly in the extracted signal data. When an anomaly is detected in the extracted signal data, a computerized service processing device receives the correlated extracted signal data from the sensor and executes one or more of an alert process to alert a user of the detected anomalies and an updating process to a correlation sub-system within the computerized service processing device, where the detected anomaly is curated and transmitted to the database of the sensor device to update the sensor correlation data stored therein.