18731020. COMMUNICATION METHOD AND APPARATUS, STORAGE MEDIUM, AND PROGRAM PRODUCT simplified abstract (HUAWEI TECHNOLOGIES CO., LTD.)
Contents
- 1 COMMUNICATION METHOD AND APPARATUS, STORAGE MEDIUM, AND PROGRAM PRODUCT
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 COMMUNICATION METHOD AND APPARATUS, STORAGE MEDIUM, AND PROGRAM PRODUCT - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Key Features and Innovation
- 1.6 Potential Applications
- 1.7 Problems Solved
- 1.8 Benefits
- 1.9 Commercial Applications
- 1.10 Prior Art
- 1.11 Frequently Updated Research
- 1.12 Questions about Secure Neural Network Training Method
- 1.13 Original Abstract Submitted
COMMUNICATION METHOD AND APPARATUS, STORAGE MEDIUM, AND PROGRAM PRODUCT
Organization Name
Inventor(s)
COMMUNICATION METHOD AND APPARATUS, STORAGE MEDIUM, AND PROGRAM PRODUCT - A simplified explanation of the abstract
This abstract first appeared for US patent application 18731020 titled 'COMMUNICATION METHOD AND APPARATUS, STORAGE MEDIUM, AND PROGRAM PRODUCT
Simplified Explanation
This patent application describes a method for improving security in a neural network training process by sending training information, aggregating local models, and updating a global model.
Key Features and Innovation
- Server sends training information including a global model and identifiers of participating terminals.
- Terminals send local models based on the global model and a shared key.
- Server aggregates local models to update the global model in the current round.
- Enhances security in neural network training processes.
Potential Applications
This technology can be applied in:
- Machine learning systems
- Data security protocols
- Collaborative training environments
Problems Solved
- Improves security in neural network training processes
- Enhances data privacy and confidentiality
- Facilitates collaborative learning among multiple terminals
Benefits
- Enhanced security in training processes
- Improved data protection
- Efficient collaboration in machine learning tasks
Commercial Applications
Title: Secure Neural Network Training Method This technology can be utilized in:
- Cybersecurity companies
- Data analytics firms
- Research institutions developing machine learning algorithms
Prior Art
Readers interested in prior art related to this technology can explore research papers on secure neural network training methods and collaborative learning in machine learning systems.
Frequently Updated Research
Stay updated on the latest advancements in secure neural network training methods and collaborative learning techniques to enhance data security and privacy.
Questions about Secure Neural Network Training Method
How does this technology improve security in neural network training processes?
This technology enhances security by sending training information, aggregating local models, and updating a global model based on shared keys, ensuring data privacy and confidentiality.
What are the potential applications of this secure neural network training method?
This method can be applied in machine learning systems, data security protocols, and collaborative training environments to enhance security and efficiency in training processes.
Original Abstract Submitted
This application discloses a communication method and apparatus, a storage medium, and a program product. The method includes: A server sends training information. The training information includes a global model in a previous round and identifiers of at least two second terminals that participate in a current round of training. A first terminal sends a local model of the first terminal. The local model is obtained based on the global model in the previous round and a shared key. The server receives local models of the at least two second terminals, and aggregates the local models of the at least two second terminals based on a shared key between the at least two second terminals, to obtain an updated global model in the current round. According to the solutions of this application, security in a neural network training process is improved.