18593496. METHOD FOR COLLABORATIVE MACHINE LEARNING simplified abstract (NOKIA SOLUTIONS AND NETWORKS OY)
Contents
METHOD FOR COLLABORATIVE MACHINE LEARNING
Organization Name
NOKIA SOLUTIONS AND NETWORKS OY
Inventor(s)
Alice Dethise of Stuttgart (DE)
Ruichuan Chen of Stuttgart (DE)
Istemi Ekin Akkus of Stuttgart (DE)
Paarijaat Aditya of Stuttgart (DE)
Antti Herman Koskela of Espoo (FI)
METHOD FOR COLLABORATIVE MACHINE LEARNING - A simplified explanation of the abstract
This abstract first appeared for US patent application 18593496 titled 'METHOD FOR COLLABORATIVE MACHINE LEARNING
The abstract describes a system that includes training units, aggregator units, and administration units implemented as trusted execution environments for collaborating data owners to store private data securely.
- Training units are responsible for storing private data and encrypted models.
- Aggregator units store and execute training algorithms for model owners.
- Administration units control communication and synchronization between training and aggregator units.
- Communication between training and aggregator units is encrypted to ensure data security.
Potential Applications: - Secure data storage and collaboration for multiple data owners. - Encrypted model training for machine learning algorithms. - Controlled communication and synchronization in a collaborative environment.
Problems Solved: - Ensuring data privacy and security in collaborative data storage. - Secure execution of training algorithms for model owners. - Controlled communication and synchronization between collaborating parties.
Benefits: - Enhanced data security and privacy protection. - Efficient collaboration and training of machine learning models. - Controlled and secure communication between collaborating parties.
Commercial Applications: Title: Secure Collaborative Data Storage System This technology can be used in industries such as healthcare, finance, and research where secure data collaboration is essential. It can also be applied in cloud computing environments for secure data sharing.
Questions about the technology: 1. How does the system ensure the privacy and security of the stored data? 2. What are the advantages of using trusted execution environments for implementing the training, aggregator, and administration units?
Original Abstract Submitted
A system comprising: at least one training unit for one or more data owners collaborating to the system for storing private data and at least one encrypted model, said training unit being implemented as a trusted execution environment; at least one aggregator unit for each model owner collaborating to the system for storing and executing code of a training algorithm, said aggregator unit being implemented as a trusted execution environment; at least one administration unit for controlling communication and synchronization between the at least one training unit and the at least one aggregator unit, said administration unit being implemented as a trusted execution environment; wherein the communication between the at least one training unit and the at least one aggregator unit is encrypted.
