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In-network generalized trustworthy data collection for event detection in cyber-physical systems.

Hafiz Ur Rahman¹, Guojun Wang¹, Md Zakirul Alam Bhuiyan²

¹School of Computer Science, Guangzhou University, Guangzhou, Guangdong Province, China.

Peerj. Computer Science

|May 20, 2021

Summary

This summary is machine-generated.

This study presents a new framework for trustworthy data collection in Cyber-Physical Systems (CPS). It ensures reliable event detection by validating sensor data locally and before aggregation, identifying faulty sensors.

Keywords:

Cyber-physical system Data collection Data dependability Data quality Data trustworthiness Event monitoring Fire detection Security and privacy

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Area of Science:

Cyber-Physical Systems (CPS)
Internet of Things (IoT)
Sensor Networks

Background:

Data collection in CPS is often unreliable due to resource constraints, environmental factors, and security issues.
Event detection in CPS is challenging without validated sensor data during acquisition, transmission, and aggregation.
Existing methods struggle to ensure data integrity and identify faulty sensors effectively.

Purpose of the Study:

To introduce a novel framework, In-network Generalized Trustworthy Data Collection (IGTDC), for reliable event detection in CPS.
To enhance data aggregation at the edge of CPS by ensuring data trustworthiness.
To identify and mitigate the impact of faulty sensors in CPS data streams.

Main Methods:

Developed the In-network Generalized Trustworthy Data Collection (IGTDC) framework.
Implemented local data validation at the sensor module before transmission.
Utilized gate-level modeling with Verilog User Defined Primitive (UDP) and Programmable Logic Device (PLD) for data validation.
Employed Gray code in gate-level modeling for enhanced data reliability and faulty sensor identification.

Main Results:

Demonstrated reliable data collection through simulations and performance analysis.
The IGTDC framework successfully validates data trustworthiness at multiple stages.
Faulty sensors were effectively identified, improving overall system reliability.

Conclusions:

The IGTDC framework significantly improves the reliability of data collection in CPS.
The proposed methods ensure trustworthy data for event detection and aggregation.
IGTDC is suitable for a wide range of Cyber-Physical Systems applications requiring dependable data.