EADC: An Efficient Anonymous Data Collection Scheme with Blockchain in Internet of Things

Area of Science:

• Blockchain Technology
• Internet of Things (IoT)
• Cryptography

Background:

• Smart contracts (SCs) on blockchain enhance IoT decentralization and trust.
• Data privacy is a critical challenge in SC-based IoT systems.
• Existing data aggregation methods lack fine-grained collection capabilities.

Purpose of the Study:

• To propose an efficient anonymous data collection (EADC) scheme for IoT environments.
• To address the limitations of current privacy-preserving methods in SC-enabled IoT.
• To enable fine-grained data collection while maintaining user anonymity.

Main Methods:

• Integration of matrix algorithms with homomorphic encryption (HE).
• Implementation of a sophisticated data grouping protocol.
• Cutting off the user-data connection during the data upload process.

Main Results:

• The EADC scheme effectively anonymizes data collection in IoT.
• Achieves efficient data gathering without compromising user privacy.
• Demonstrates improved system efficiency through data grouping.

Conclusions:

• The proposed EADC scheme offers a viable solution for privacy-preserving data collection in IoT.
• Combines advanced cryptographic techniques for robust data security.
• Facilitates the secure and efficient evolution of SC-integrated IoT systems.