DECENTRALIZED TRUST AND CONSENSUS MECHANISMSFOR PROTECTING SENSITIVE DATA IN DISTRIBUTED SYSTEMS

Abstract

B a c k g r o u n d . The study addresses the rapid expansion of data processed within distributed digital ecosystems, where traditional centralized storage models introduce risks due to single points of failure and limited transparency in monitoring changes. The need is emphasized for secure, resilient, and verifiable mechanisms capable of protecting sensitive information in dynamic multi-user environments. M e t h o d s . A hybrid blockchain architecture integrating public and private ledgers is developed. A mathematical model of decentralized data protection is formalized, digital signatures, smart contracts, and cryptographic hashing are applied, and a functional prototype is implemented using Hyperledger Fabric with the RAFT consensus algorithm to validate secure access and ensure transaction integrity. R e s u l t s . Analytical modeling and simulation experiments involving networks of 10–100 nodes demonstrate increased system resilience by approximately 20–25% while maintaining stable transaction latency. The implemented model reliably detects unauthorized access attempts and modification actions and shows compliance with international standards, including ISO/IEC 27001 and GDPR. C o n c l u s i o n s . The findings confirm that blockchain-based architectures can significantly enhance data security in distributed environments and surpass traditional centralized protection models. The proposed framework ensures integrity, transparency, and traceability with minimal performance degradation, making it suitable for financial, governmental, medical, and corporate systems. Further development is considered promising in the context of integrating machine learning, quantum resistant cryptography, and cloud infrastructures.