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A two-phase spatiotemporal chaos-based protocol for data integrity in IoT.

Mimouna Abdullah Alkhonaini¹, Farhan A Alenizi², Yahia Hasan Jazyah³

¹Department of Computer Science, College of Computer and Information Sciences, Prince Sultan University, Riyadh, Saudi Arabia.

Scientific Reports

|April 15, 2024

Summary

This study introduces a novel data integrity method for Internet of Things (IoT) applications. The new protocol enhances security and efficiency, reducing energy consumption and packet overhead without third-party auditors.

Keywords:

Chaos theory Integrity ensuring Internet of Things Network security Secure data transmission

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Area of Science:

Computer Science
Cybersecurity
Network Engineering

Background:

Data integrity is a critical challenge in expanding Internet of Things (IoT) applications across industries.
Existing data integrity solutions for IoT often face limitations in efficiency and cost-effectiveness.

Purpose of the Study:

To propose a novel, secure, and efficient data integrity methodology for Internet of Things applications.
To address the limitations of conventional data integrity protocols in IoT environments.

Main Methods:

The proposed protocol involves two stages: "sequence sharing" and "data exchange."
The "sequence sharing" stage utilizes a chaotic model for secure identity exchange and common sequence generation between nodes.
The "data exchange" stage focuses on packet validation, leveraging authentication and timing calculations from the first stage.

Main Results:

The new methodology demonstrates effectiveness in ensuring data integrity across various testing scenarios.
Compared to conventional IoT data integrity protocols, the proposed method is more efficient and cost-effective.
The approach significantly reduces energy consumption and packet overhead, eliminating the need for third-party auditors.

Conclusions:

The proposed data integrity methodology is a robust and practical solution for Internet of Things applications.
The method offers enhanced security against diverse threats.
It presents a viable, cost-effective, and energy-efficient alternative for ensuring data integrity in IoT.