International business machines corporation (20240291864). INTRUSION DETECTION BASED ON IMPLICIT ACTIVE LEARNING simplified abstract
Contents
INTRUSION DETECTION BASED ON IMPLICIT ACTIVE LEARNING
Organization Name
international business machines corporation
Inventor(s)
Oded Sofer of Midreshet Cen Gurion (IL)
INTRUSION DETECTION BASED ON IMPLICIT ACTIVE LEARNING - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240291864 titled 'INTRUSION DETECTION BASED ON IMPLICIT ACTIVE LEARNING
The abstract describes a computer-implemented method for monitoring a honeypot trap environment to detect unauthorized intrusion attempts.
- Automatically monitoring a honeypot trap environment to capture activity data within it
- Extracting attributes from the captured data representing entities, events, and relations
- Applying an analytics suite to identify specific combinations of attributes associated with unauthorized intrusion attempts
- Assigning risk scores to these combinations based on the likelihood of intrusion attempts
- Generating security rules for an intrusion detection and prevention system based on the identified combinations
Potential Applications: - Enhancing cybersecurity measures - Improving threat detection capabilities - Strengthening network security
Problems Solved: - Identifying and mitigating unauthorized intrusion attempts - Enhancing overall cybersecurity posture - Improving incident response capabilities
Benefits: - Proactive threat detection - Enhanced security measures - Improved incident response times
Commercial Applications: Title: "Advanced Intrusion Detection and Prevention System" This technology can be utilized by cybersecurity firms, IT departments, and organizations looking to bolster their network security measures. It can also be integrated into existing security systems to enhance threat detection capabilities.
Questions about the technology: 1. How does this method differ from traditional intrusion detection systems? - This method focuses on monitoring honeypot trap environments specifically designed to attract unauthorized intrusion attempts, allowing for more targeted threat detection. 2. What are the key advantages of using a honeypot trap environment for threat detection? - Honeypot trap environments provide a controlled setting to capture and analyze malicious activity, enabling organizations to proactively identify and mitigate potential security threats.
Original Abstract Submitted
a computer-implemented method comprising: automatically monitoring a honeypot trap environment, to capture activity data within the honeypot trap environment, wherein the honeypot trap environment comprises a plurality of software and hardware resources that are intended to attract attempts at unauthorized use of the honeypot trap environment; automatically extracting, from the captured activity data, a plurality of attributes representing entities, events, and relations between the entities and events; automatically applying an analytics suite to identify specific combinations of the attributes as representing a likelihood of being associated with an unauthorized intrusion attempt into the honeypot environment; automatically assigning a risk score to each of the specific combinations, wherein the risk score reflect the likelihood of being associated with an unauthorized intrusion attempt into the honeypot environment; and automatically generating at least one security rule for an intrusion detection and prevention system, based on at least one of the specific combinations.
