International business machines corporation (20240129178). TOPOLOGY-HOMOGENEITY FOR ENRICHING EVENT PATTERNS IN ARTIFICIAL INTELLIGENCE OPERATIONS simplified abstract
Contents
- 1 TOPOLOGY-HOMOGENEITY FOR ENRICHING EVENT PATTERNS IN ARTIFICIAL INTELLIGENCE OPERATIONS
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 TOPOLOGY-HOMOGENEITY FOR ENRICHING EVENT PATTERNS IN ARTIFICIAL INTELLIGENCE OPERATIONS - 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
TOPOLOGY-HOMOGENEITY FOR ENRICHING EVENT PATTERNS IN ARTIFICIAL INTELLIGENCE OPERATIONS
Organization Name
international business machines corporation
Inventor(s)
Mudhakar Srivatsa of White Plains NY (US)
Jonathan Ian Settle of Dursley (GB)
Satishkumar Sadagopan of Leawood KS (US)
Mathews Thomas of Flower Mound TX (US)
TOPOLOGY-HOMOGENEITY FOR ENRICHING EVENT PATTERNS IN ARTIFICIAL INTELLIGENCE OPERATIONS - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240129178 titled 'TOPOLOGY-HOMOGENEITY FOR ENRICHING EVENT PATTERNS IN ARTIFICIAL INTELLIGENCE OPERATIONS
Simplified Explanation
The patent application describes a method for determining correlations of events occurring in multiple nodes of a network by associating events with related events on other nodes based on address information.
- Access address information of nodes on a network
- Access event IDs associated with events on nodes
- Create associations between events on different nodes based on address information
Potential Applications
This technology could be applied in:
- Network monitoring and analysis
- Cybersecurity threat detection
- Predictive maintenance in IoT systems
Problems Solved
This technology helps in:
- Identifying correlations between events on different nodes
- Improving network performance and security
- Streamlining data analysis processes
Benefits
The benefits of this technology include:
- Enhanced network visibility
- Early detection of potential issues
- Efficient troubleshooting and problem resolution
Potential Commercial Applications
This technology could be commercially benefit:
- Network security companies
- IoT device manufacturers
- Data analytics firms
Possible Prior Art
One possible prior art could be a similar method used in data analytics software to correlate events across different data sources.
What are the potential limitations of this method in correlating events across nodes in a network?
The potential limitations of this method could include:
- Scalability issues with a large number of nodes
- Accuracy of event correlation in complex network environments
How does this method ensure data privacy and security while accessing address information and event IDs from multiple nodes?
This method can ensure data privacy and security by:
- Implementing encryption protocols for data transmission
- Restricting access to sensitive information through authentication mechanisms
Original Abstract Submitted
a method for determining a correlation of one or more events occurring in a plurality of nodes of a network includes accessing, by a computing device, address information associated with each of the plurality of nodes on the network. the computing device can further access one or more event ids associated with one or more events occurring on the plurality of nodes. the computing device can further create an association the one or more events occurring on the plurality of nodes with related events occurring on others of the plurality of nodes, the association including the address information.
