Malicious Anchor Node Detection in Wireless Sensor Networks
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Solution Overview
Problem
Existing wireless sensor network localization methods are prone to errors due to malicious anchor nodes, which are difficult to detect and correct, especially in harsh and unstable environments with high attack intensity, leading to inaccurate node localization.
Innovation Solution
A method that recovers sparse terms by establishing an unknown disturbance term, using a recursive weighted linear least square method, and self-adaptive gradient projection to detect malicious anchor nodes and estimate target node localization simultaneously, improving detection accuracy and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional localization methods are used in wireless sensor networks, then node localization can be achieved, but the accuracy deteriorates due to malicious anchor nodes providing error location information
Solution Approach 1:
The patent segments the localization problem into two independent parts: (1) detecting malicious anchor nodes by analyzing the consistency of their provided location information, and (2) performing localization using only verified benign anchor nodes. This segmentation allows the system to identify and isolate malicious nodes before they can corrupt the localization results, thereby maintaining both high accuracy and reliability
Solution Approach 2:
The patent performs preliminary detection of malicious anchor nodes before the actual localization process. By first verifying the authenticity of anchor node information and screening out malicious nodes in advance, the system prevents corrupted data from affecting the final localization accuracy, thus resolving the contradiction between measurement precision and reliability
2Reliability
If malicious anchor node detection is performed separately from localization, then detection accuracy can be improved, but time complexity increases due to multiple processing stages
Solution Approach 1:
The patent merges the malicious node detection process with the localization process into a unified framework. The detection of malicious anchor nodes and the localization of target nodes are performed simultaneously in one stage, rather than as separate sequential processes. This integration maintains high detection accuracy while significantly reducing time complexity by eliminating the need for multiple processing stages
Data Source
AI summary
A malicious anchor node detection and target node localization method based on recovery of sparse terms, includes: S1: establishing an unknown disturbance term by using ranging value attack terms from an attacker to nodes in a wireless sensor network, and introducing a to-be-estimated location of a target node to the unknown disturbance term, to obtain an unknown sparse vector; S2: converting a problem of malicious anchor node detection and target node localization into a problem of recovery of the unknown sparse vector; S3: determining a location of an initial node according to a recursive weighted linear least square method, and recovering and reconstructing the unknown sparse vector with sparsity; and S4: determining a malicious anchor node determination range by approximating a threshold using a recovered value of the unknown sparse vector, to implement malicious anchor node detection, and recovering and determining location information of the target node.