17946859. MANAGING UNTRUSTED USER EQUIPMENT (UES) FOR DATA COLLECTION simplified abstract (QUALCOMM Incorporated)
Contents
- 1 MANAGING UNTRUSTED USER EQUIPMENT (UES) FOR DATA COLLECTION
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 MANAGING UNTRUSTED USER EQUIPMENT (UES) FOR DATA COLLECTION - 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 Original Abstract Submitted
MANAGING UNTRUSTED USER EQUIPMENT (UES) FOR DATA COLLECTION
Organization Name
Inventor(s)
Mohamed Fouad Ahmed Marzban of San Diego CA (US)
Wooseok Nam of San Diego CA (US)
MANAGING UNTRUSTED USER EQUIPMENT (UES) FOR DATA COLLECTION - A simplified explanation of the abstract
This abstract first appeared for US patent application 17946859 titled 'MANAGING UNTRUSTED USER EQUIPMENT (UES) FOR DATA COLLECTION
Simplified Explanation
The patent application describes methods, systems, and devices for wireless communications where a network entity determines the trustworthiness of information provided by a user equipment (UE) based on a machine learning model. If the information is deemed untrusted, the network entity may indicate this to another network entity, which can then train the machine learning model using only trusted information and configure the UE to stop data collection processes if it is deemed untrusted.
- The network entity determines the trustworthiness of information provided by a UE based on a machine learning model.
- If the information is considered untrusted, the network entity can indicate this to another network entity.
- The other network entity can then train the machine learning model using only trusted information and configure the UE to stop data collection processes if it is deemed untrusted.
Potential Applications
This technology could be applied in various industries where data security and trustworthiness are crucial, such as telecommunications, IoT, and data analytics.
Problems Solved
This technology addresses the issue of ensuring the trustworthiness of information provided by UEs in wireless communication systems, enhancing data security and reliability.
Benefits
- Improved data security and trustworthiness in wireless communication systems - Enhanced reliability of machine learning models used in network entities - Efficient management of data collection processes in UEs
Potential Commercial Applications
"Enhancing Data Security in Wireless Communications: Applications and Benefits"
Possible Prior Art
There may be prior art related to data security and trustworthiness in wireless communication systems, but specific examples are not provided in the abstract.
Unanswered Questions
== How does this technology impact the overall performance of wireless communication systems? This technology could potentially improve the overall performance of wireless communication systems by enhancing data security and reliability.
== What are the potential challenges in implementing this technology on a large scale? Some potential challenges in implementing this technology on a large scale may include ensuring compatibility with existing systems, addressing privacy concerns, and managing the training of machine learning models efficiently.
Original Abstract Submitted
Methods, systems, and devices for wireless communications are described. In some systems, a network entity may obtain information (e.g., a data set, a model update) corresponding to a user equipment (UE), the information associated with a machine learning model. The network entity may determine whether the information or the UE providing the information is trusted or untrusted based on the information. The network entity may output, to another network entity, an indication that the information corresponding to the UE is considered untrusted or trusted based on a predicted output of the machine learning model (e.g., if the model is trained using the information). The other network entity may further train the machine learning model using trusted information and may refrain from using untrusted information. Additionally, or alternatively, if a UE is determined to be untrusted, a network entity may configure the UE to refrain from further data collection processes.
