Centralized Duplicate Removal Video Storage System with Privacy Preservation in IoT

Area of Science:

• Computer Science
• Information Security
• Cloud Computing

Background:

• The Internet of Things (IoT) generates vast amounts of sensitive data, necessitating efficient cloud storage solutions.
• Data deduplication is crucial for reducing bandwidth and storage in IoT but is hindered by encryption required for privacy.
• Existing methods struggle to balance privacy protection with effective deduplication in untrusted cloud environments.

Purpose of the Study:

• To develop a centralized storage system for IoT that enables privacy-preserving duplicate removal.
• To address the challenge of performing data deduplication on encrypted data without compromising user privacy.
• To enhance the security and efficiency of data storage in IoT environments.

Main Methods:

• Implementation of a centralized duplicate removal system supporting file-level and block-level deduplication.
• Utilization of Intel Software Guard Extensions (SGX) to secure the deduplication process on the cloud server.
• Encryption of data before uploading to cloud servers to protect sensitive user information.

Main Results:

• The proposed system significantly improves deduplication efficiency in IoT cloud storage.
• Enhanced security is achieved by protecting the deduplication process from potential breaches.
• The system effectively handles encrypted data, overcoming a major obstacle in secure deduplication.

Conclusions:

• The developed privacy-preserving duplicate removal system is highly effective for centralized IoT storage.
• Intel SGX technology provides a robust solution for secure deduplication of sensitive IoT data.
• This approach offers a promising direction for secure and efficient data management in the expanding IoT landscape.