AI Platform for Cyber Threat Detection
A New Alternative of Cyber Threat Detection, eyeCloudAI
AI discovers hidden security threats and distinguishes false positives of events that occurred in the previous system.
Increased Scope of Cyber Threat Detection
and Response Range
AI only takes a few seconds to analyze when it takes at least 10 minutes for manual analysis
Instead of manpower, AI performs anomaly detection and false-positive distinguishing
which improve security threat responsive rate.
Note: It is a real use case of customer A with 40 thousand systems.
For the smaller IT infrastructure and less synced devices detection scope and time improve.
Proven track record of high accuracy and efficiency from Korea’s largest security management systems
99.8% detection rate and accuracy
More than 10 years of attack data and in-house white hackers’ new attack data are fed into the repetitive and reinforced learning for AI models. This results in a high detection rate and accuracy.
Note: It is a real use case of a governmental agency A.
An equivalent of 15 times more servers added
AI model’s virtualization and juxtaposed distribution processing technology operate in 15 virtual POD simultaneously. Introduction of 1 model creates equivalent efficiency of adding 15 hardware.
- Threat and normal data collection
- Anomaly detection model and false-positive analysis model are created by machine learning based on the collected data
- Machine learning for Threat analysis and detection
- Updates data and learning methods based on the results of learning
- Reinforcement learning improves detection rate and accuracy
- Based on the results of analysis and detection, operators intervene responses and further action
- Reinforcement learning and application using new threat data
- New model creation and management
- Real-time analysis and detection by AI models
- Anomaly detection (Unknown threat)
- False-positive analysis and distinguishing