18472059. SELF-LEARNING EGRESS TRAFFIC CONTROLLER simplified abstract (Juniper Networks, Inc.)
Contents
- 1 SELF-LEARNING EGRESS TRAFFIC CONTROLLER
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 SELF-LEARNING EGRESS TRAFFIC CONTROLLER - 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
SELF-LEARNING EGRESS TRAFFIC CONTROLLER
Organization Name
Inventor(s)
Raja Kommula of Cupertino CA (US)
Ganesh Byagoti Matad Sunkada of Bengaluru (IN)
Tarun Banka of Milpitas CA (US)
Thayumanavan Sridhar of Sunnyvale CA (US)
Raj Yavatkar of Los Gatos CA (US)
SELF-LEARNING EGRESS TRAFFIC CONTROLLER - A simplified explanation of the abstract
This abstract first appeared for US patent application 18472059 titled 'SELF-LEARNING EGRESS TRAFFIC CONTROLLER
Simplified Explanation
The abstract describes a network system that can detect and notify anomalous egress connections of an application service.
- The network system includes processing circuitry and memories for storing instructions.
- The instructions, when executed, allow the system to receive connection data related to an egress connection of an application service.
- The system analyzes the connection data to identify anomalous egress connections.
- Upon detecting an anomalous connection, the system generates a notification and sends it to a computing device.
Potential Applications
This technology could be applied in cybersecurity systems to detect and prevent unauthorized data exfiltration attempts.
Problems Solved
This technology helps in identifying and notifying about anomalous egress connections, which can be indicative of security breaches or unauthorized access.
Benefits
The system provides real-time monitoring and alerts for potential security threats, enhancing the overall security posture of the network.
Potential Commercial Applications
"Enhancing Network Security with Anomalous Egress Connection Detection"
Possible Prior Art
One possible prior art could be intrusion detection systems that monitor network traffic for suspicious activities and generate alerts in case of anomalies.
Unanswered Questions
How does the system differentiate between normal and anomalous egress connections?
The system likely uses a set of predefined rules or machine learning algorithms to analyze the connection data and identify patterns indicative of anomalous behavior.
What measures are in place to ensure the accuracy and reliability of the notifications generated by the system?
The system may incorporate validation mechanisms and thresholds to reduce false positives and ensure that only genuine security incidents trigger notifications.
Original Abstract Submitted
An example network system includes processing circuitry and one or more memories coupled to the processing circuitry. The one or more memories are configured to store instructions which, when executed by the processing circuitry, cause the network system to receive connection data related to an egress connection of an application service of an application. The instructions cause the network system to analyze the connection data to determine that the egress connection is an anomalous connection. The instructions cause the network system to generate a notification indicative of the egress connection being an anomalous connection and send the notification to a computing device.
