Investigations into a Cross-Domain Authentication Model for Cloud Computing, Utilizing a Dynamically Sharded Masterchain-Sidechain Hybrid Architecture for Enhanced Privacy-Regulatory Equilibrium

Abstract

This study proposes a dynamic main-chain-side-chain hybrid architecture to address the privacy leakage risk (68% APT attack probability) and efficiency bottleneck (42% OAuth2.0 failure rate) in conventional cross-domain authentication systems in cloud computing, focusing on resolving the performance-privacy-regulation paradox. The creation of decentralized authentication involves constructing a multi-layered structure: the primary chain layer utilizes PoS consensus and SHA-3 algorithm to manage identity registration delays at 120ms; the secondary layer employs ShardedBFT dynamic slicing technology (θ=0.85) for over 2000 TPS authentication; and the interface layer merges ZK-SNARKs with the NIST P-256 algorithm, cutting down communication costs by 33%. By integrating ZK-SNARKs with the NIST P-256 algorithm, the interface layer achieves a 33% decrease in communication overhead. The novel node credit model (Rj=0.6Aj+0.3Bj+0.1Cj) accomplishes sharding restructuring in less than 2.3 seconds, enhances the MPT protocol by 30%, and boosts regulatory traceability precision to 99.2% through a risk-adaptive contract (Wd=0.7Td+0.3Hd). Research indicates that the system exhibits a delay of 105±4ms in a 10k simultaneous stress test (19% less than the ideal control group), enhances Byzantine fault tolerance by 8% to 33%, boosts defense against Sybil attacks by 98%, and boosts patient recovery rates by 22% through reducing the duration for retrieving inter-hospital medical records to 5 minutes of critical emergency time in medical situations. Research demonstrates the architecture’s ability to maintain a balance between k=5 anonymity and 99.2% traceability, offering a robust security approach for cross-domain authentication. Going forward, our plan is to amalgamate federated learning with HarmonyOS cross-chain technology to enhance the resolution of consensus delays and errors in credit evaluation.