Homomorphic Asymmetric Encryption Applied to the Analysis of IoT Communications

Area of Science:

• Computer Science
• Cryptography
• Sensor Networks

Background:

• Sensor networks generate vast amounts of data crucial for various sectors, including agribusiness.
• Ensuring data confidentiality and integrity during transmission and processing is a significant challenge.
• Existing methods for data quality assessment often require decryption, hindering real-time analysis and privacy.

Purpose of the Study:

• To explore the application of homomorphic encryption for secure sensor data processing.
• To enable real-time data quality assessment of sensor nodes without data decryption.
• To enhance the security and privacy of sensor network data within blockchain infrastructures.

Main Methods:

• Utilizing homomorphic encryption techniques to encrypt sensor data.
• Developing statistical methods to analyze encrypted data for detecting sensor anomalies.
• Integrating these methods within a blockchain infrastructure for sensor network management.

Main Results:

• Demonstrated the feasibility of performing statistical computations on encrypted sensor data.
• Achieved real-time detection of sensor malfunctions (e.g., malicious injection, damage) using encrypted data.
• Eliminated the need for decryption and shared key infrastructure, improving efficiency and privacy.

Conclusions:

• Homomorphic encryption offers a viable solution for secure and private real-time analysis of sensor data.
• The proposed technique is effective for data quality control in critical applications like agribusiness.
• The method supports privacy-preserving operations within blockchain-based sensor networks.