Blockchain Processing Technique Based on Multiple Hash Chains for Minimizing Integrity Errors of IoT Data in Cloud...

Area of Science:

• Computer Science
• Data Science
• Cybersecurity

Background:

• Internet of Things (IoT) devices generate vast amounts of data across diverse sectors, necessitating secure and reliable data handling.
• Current cloud-based data storage for IoT is vulnerable to integrity issues from errors, security attacks, and environmental factors.
• Direct cloud storage limits control and data integrity assurance for distributed IoT deployments.

Purpose of the Study:

• To propose an optimized hash processing technique for hierarchical distributed processing of IoT data.
• To enhance the integrity and reliability of IoT data stored in distributed cloud environments.
• To improve the efficiency and load balancing of IoT data management using blockchain technology.

Main Methods:

• Developed an n-bit blockchain-based optimized hash processing technique for hierarchical distributed data processing.
• Implemented interactive authentication between n, n+1, and n-1 blockchain layers to validate IoT data.
• Validated hash values of IoT data and their index information stored across distributed locations within the blockchain.

Main Results:

• Reduced IoT data processing time by an average of 2.54 times.
• Improved blockchain generation time by 17.3% during IoT data linking.
• Enhanced asymmetric storage efficiency (6.9%) and speed (10.3%) based on hash code length.
• Increased IoT data integrity accuracy by an average of 18.3% compared to existing methods.

Conclusions:

• The proposed technique effectively minimizes IoT data integrity errors in distributed cloud environments.
• Blockchain-enabled hierarchical processing and interactive authentication strengthen data reliability and security.
• The method optimizes load balancing and ensures efficient linkage of IoT data, improving overall system performance.