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The framework employs homomorphic encryption (HE) and differential privacy (DP) to safeguard sensitive data during the learning process
WiMi Hologram Cloud has introduced a groundbreaking blockchain-based framework, dubbed Trusted Collaborative Learning (TrusCL), designed to enhance the security and efficiency of collaborative learning in Internet of Things (IoT) environments. TrusCL addresses the stringent privacy and computational demands of Artificial Intelligence of Things (AIoT) applications by integrating advanced data protection techniques.
The framework employs homomorphic encryption (HE) and differential privacy (DP) to safeguard sensitive data during the learning process. Homomorphic encryption enables direct computation on encrypted data, eliminating the need for decryption and thus reducing the risk of data exposure. Simultaneously, differential privacy adds random noise to datasets, ensuring that individual information remains confidential even when subjected to external queries. Blockchain technology further enhances the TrusCL framework by recording all key activities, such as model updates and data contributions, on an immutable ledger. This transparency and traceability prevent dishonest practices, with smart contracts automatically enforcing compliance with predefined rules.
The TrusCL framework provides a secure platform for model training, allowing data owners to contribute without exposing their data directly. It also includes dynamic reward mechanisms to incentivize high-quality data contributions, improving model accuracy and generalization. WiMi’s innovative approach sets a new standard for secure collaborative learning in the AIoT era, paving the way for more secure and efficient data sharing and analysis in the ongoing development of Industry 4.0.
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