A Novel Privacy Preserving Scheme for Smart Grid-Based Home Area Networks

Area of Science:

• Computer Science
• Electrical Engineering
• Cybersecurity

Background:

• Smart grids offer benefits but face security and privacy challenges due to heterogeneous device communication over public networks.
• Internet of Things (IoT)-enabled smart homes raise significant privacy concerns for researchers and users.
• Home Area Networks (HAN) within smart grids require robust security measures for data aggregation and transmission.

Purpose of the Study:

• To propose a novel privacy-preserving method for smart grid-based HAN.
• To address security and privacy concerns in IoT-enabled smart homes.
• To enable early detection of false data injection and replay attacks within the HAN.

Main Methods:

• Utilizing homomorphic Paillier encryption for secure data aggregation.
• Applying the Chinese Remainder Theorem to enhance data processing.
• Implementing a one-way hash function for data integrity and attack detection.
• Designing a sink node capable of data aggregation and attack detection.

Main Results:

• The proposed method effectively aggregates data from diverse household appliances while preserving privacy.
• The sink node successfully detects false data injection and replay attacks.
• Security analysis confirms the proposed approach provides adequate security for smart grid HAN.

Conclusions:

• The novel privacy-preserving method enhances security and privacy in smart grid HAN.
• The integration of encryption, CRT, and hashing provides a robust solution for IoT smart home security.
• The approach contributes to building trust and transparency in smart grid communication.