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A Lightweight IDS Based on Blockchain and Machine Learning for Detecting Physical Attacks in Wireless Sensor

Maytham S Jabor¹, Aqeel S Azez¹, José Carlos Campelo¹

¹ITACA Institute, Universitat Politècnica de València (UPV), Camino de Vera s/n, 46022 Valencia, Spain.

Sensors (Basel, Switzerland)

|March 28, 2026

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This study introduces a novel two-layer intrusion detection system (IDS) for wireless sensor networks (WSNs). The system integrates blockchain (BC) and artificial neural networks (ANN) to effectively detect physical attacks, enhancing network security.

Area of Science:

Computer Science
Cybersecurity
Network Security

Background:

Wireless sensor networks (WSNs) face significant security risks from physical attacks compromising data integrity.
Existing security solutions often demand high computational resources, unsuitable for resource-limited WSN devices.

Purpose of the Study:

To propose a lightweight, two-layer intrusion detection system (IDS) for WSNs.
To enhance WSN security against physical attacks by integrating blockchain (BC) and machine learning (ML).

Main Methods:

A two-layer IDS architecture combining a lightweight BC protocol for cluster heads (CHs) and base station (BS) with an artificial neural network (ANN) at the BS.
The BC layer uses hash-based consensus for data integrity checks, while the ANN layer detects sophisticated attacks bypassing BC verification.

Keywords:

ANN IDS WSN blockchain intrusion detection lightweight physical attack

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The system is designed to minimize processing load on individual sensor nodes.

Main Results:

The proposed IDS achieved high performance metrics, including 97.42% accuracy and 98.35% recall in simulations.
The system demonstrated superior performance compared to five established classifiers and standalone BC or ANN components.
It maintained robust detection rates above 99.98% even with 30 simultaneous attackers and tolerated up to 10% packet loss.

Conclusions:

The integrated BC and ANN approach offers an effective and lightweight solution for physical attack detection in WSNs.
This system significantly improves WSN security without overburdening resource-constrained sensor nodes.
The proposed IDS provides a scalable and reliable security framework for WSNs facing advanced threats.