Dell products l.p. (20240177025). SYSTEM AND METHOD FOR MANAGING DATA PROCESSING SYSTEMS HOSTING DISTRIBUTED INFERENCE MODELS simplified abstract
Contents
- 1 SYSTEM AND METHOD FOR MANAGING DATA PROCESSING SYSTEMS HOSTING DISTRIBUTED INFERENCE MODELS
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 SYSTEM AND METHOD FOR MANAGING DATA PROCESSING SYSTEMS HOSTING DISTRIBUTED INFERENCE MODELS - 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
SYSTEM AND METHOD FOR MANAGING DATA PROCESSING SYSTEMS HOSTING DISTRIBUTED INFERENCE MODELS
Organization Name
Inventor(s)
OFIR Ezrielev of Beer Sheva (IL)
JEHUDA Shemer of Kfar Saba (IL)
SYSTEM AND METHOD FOR MANAGING DATA PROCESSING SYSTEMS HOSTING DISTRIBUTED INFERENCE MODELS - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240177025 titled 'SYSTEM AND METHOD FOR MANAGING DATA PROCESSING SYSTEMS HOSTING DISTRIBUTED INFERENCE MODELS
Simplified Explanation
The patent application describes methods and systems for managing inference models hosted by data processing systems. These systems are monitored for potential compromise, and if a compromise is detected, a self-healing or remediation process is initiated to mitigate the threat to successful inference generation.
- Data processing systems hosting inference models are monitored for risk of compromise.
- Monitoring involves evaluating processing results to identify compromised systems.
- When a compromised system is detected, a self-healing or remediation process is initiated to address the threat.
Potential Applications
The technology described in the patent application could be applied in various industries where data processing systems host critical inference models, such as healthcare, finance, cybersecurity, and autonomous vehicles.
Problems Solved
This technology addresses the problem of compromised data processing systems affecting the successful generation of inferences, which could lead to incorrect decisions or outcomes based on the inference models.
Benefits
The benefits of this technology include enhanced security and reliability of inference models, reduced risk of compromised systems impacting decision-making processes, and improved overall system performance.
Potential Commercial Applications
Potential commercial applications of this technology include security software for data processing systems, monitoring tools for inference model hosting, and consulting services for organizations looking to enhance the security of their data processing infrastructure.
Possible Prior Art
One possible prior art could be existing systems that monitor the security of data processing systems but may not specifically focus on inference model hosting and the self-healing processes described in the patent application.
What are the specific self-healing processes initiated when a compromised system is detected?
The specific self-healing processes initiated when a compromised system is detected could include isolating the compromised system from the network, restoring the system to a known good state from backups, and implementing security patches to prevent future compromises.
How does the monitoring of processing results help in identifying compromised data processing systems?
Monitoring processing results helps in identifying compromised data processing systems by analyzing deviations from expected outcomes, abnormal processing patterns, or unauthorized access attempts that could indicate a compromise. By comparing processing results against predefined benchmarks, anomalies can be detected and investigated further.
Original Abstract Submitted
methods and systems for managing inference models hosted by data processing systems are disclosed. to manage the inference models, data processing systems that host the inference models may be monitored for risk of compromise. the data processing systems may be monitored by evaluating the processing results generated by the data processing systems. when a data processing system is identified as being compromised, a self-healing process or other remediation process may be initiated to reduce or eliminate the threat to successful inference generation presented by the compromised data processing system.
