18480318. DISTRIBUTED MACHINE LEARNING SOLUTION FOR ROGUE BASE STATION DETECTION simplified abstract (Nokia Technologies Oy)
Contents
- 1 DISTRIBUTED MACHINE LEARNING SOLUTION FOR ROGUE BASE STATION DETECTION
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 DISTRIBUTED MACHINE LEARNING SOLUTION FOR ROGUE BASE STATION DETECTION - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Unanswered Questions
- 1.11 Original Abstract Submitted
DISTRIBUTED MACHINE LEARNING SOLUTION FOR ROGUE BASE STATION DETECTION
Organization Name
Inventor(s)
Koffi Ismael Ouattara of Nozay (FR)
DISTRIBUTED MACHINE LEARNING SOLUTION FOR ROGUE BASE STATION DETECTION - A simplified explanation of the abstract
This abstract first appeared for US patent application 18480318 titled 'DISTRIBUTED MACHINE LEARNING SOLUTION FOR ROGUE BASE STATION DETECTION
Simplified Explanation
The patent application describes an apparatus that can distribute partitions of a machine learning model to different user equipments, record measurements for a cell, receive messages about handover failures, and determine if a base station is rogue based on detection reports.
- The apparatus distributes partitions of a machine learning model to user equipments.
- It records measurements for a cell and receives messages about handover failures.
- It uses machine learning model partitions to determine if a base station is rogue based on detection reports.
Potential Applications
This technology could be applied in telecommunications networks to improve handover processes and detect rogue base stations.
Problems Solved
This technology helps in optimizing handover processes in cellular networks and enhances security by identifying rogue base stations.
Benefits
The benefits of this technology include improved network efficiency, enhanced security measures, and better overall performance of cellular networks.
Potential Commercial Applications
One potential commercial application of this technology could be in the telecommunications industry for network optimization and security enhancement.
Possible Prior Art
One possible prior art could be related to machine learning models for network optimization and security in telecommunications systems.
Unanswered Questions
How does the apparatus handle handover failures effectively?
The apparatus receives messages about handover failures, but the specific methods for handling these failures are not detailed in the abstract.
What types of detection reports are used to determine if a base station is rogue?
The abstract mentions using a second partition of the machine learning model to determine if a base station is rogue, but it does not specify the exact types of detection reports used for this purpose.
Original Abstract Submitted
An apparatus configured to: obtain an indication of partitions of a machine learning model corresponding to respective ones of the one or more groups; transmit, to the respective ones of the plurality of user equipments, a corresponding partition, of the partitions of the machine learning model; transmit, to the plurality of user equipments, an indication to record measurements for the first cell; receive, from at least one of the plurality of user equipments, at least one message regarding a handover failure, wherein the at least one message comprises a message generated using a first partition of the partitions of the machine learning model; and determine, with a second partition of the partitions of the machine learning model, whether the first cell is a rogue base station based, at least partially, on a plurality of detection reports.
