Blockchain Secures Private Cloud Deduplication and Auditing, Eliminating Trusted Third Parties
This research introduces a blockchain-smart contract system using identity-based broadcast encryption to enable private, verifiable cloud data deduplication and auditing, removing central trust.
In-Memory Processing Revolutionizes Private Information Retrieval Efficiency and Scalability
IM-PIR leverages Processing-in-Memory to overcome PIR's memory-bound limitations, significantly boosting query throughput.
ZKPoT Secures Federated Learning, Ensuring Privacy and Efficiency in Decentralized Systems
A novel Zero-Knowledge Proof of Training (ZKPoT) consensus validates model performance privately, enabling scalable, secure federated learning.
Regulatable Privacy-Preserving Smart Contracts Balance Confidentiality and Oversight
A novel framework enables selective data disclosure and regulatory traceability in account-based smart contracts, advancing privacy for decentralized applications.
VeriLLM Enables Efficient, Secure, and Verifiable Decentralized LLM Inference
This research introduces a hybrid verification protocol for decentralized large language model inference, combining empirical checks with cryptographic guarantees to ensure output correctness with minimal overhead, thereby enabling trustworthy AI at scale.
Redactable Blockchains Balance Immutability with Practical Data Modification Requirements
Redactable blockchains introduce controlled data mutability via cryptographic primitives, unlocking compliance and flexibility for real-world applications.
Zero-Knowledge Proof-Based Consensus Secures Federated Learning Privacy and Efficiency
A novel Zero-Knowledge Proof of Training consensus mechanism secures federated learning, validating model performance privately while enhancing blockchain efficiency.
ECDSA-based Anonymous Credentials Enhance Digital Identity Privacy and Efficiency
New ECDSA-based anonymous credentials offer unprecedented efficiency for privacy-preserving digital identity, bypassing costly infrastructure changes for broad adoption.
Optimizing Semantic Data Storage in Distributed Ledger Technologies
This research systematically evaluates DLT types for semantic data storage, revealing private DLTs' efficiency and hybrid models' balanced utility.
