SPiDER TM AI Edition
Machine learning based preemptive response and increased prediction capabilities through AI systems
What is SPiDER TM AI Edition?
The IT environment is becoming more complex due through various technological innovations such as; wide scale, IT Infrastructure, explosive increase in data, complex compliances, tightening of laws concerning IT. Alongside this development, cyber-attacks have become more threatening through automatized hacking attacks, intelligent security threats, indiscriminate attacks and the increasing danger of cyberwarfare. Now is the time for AI based security management. AI will allow users to respond and keep up with the exponentially expanding hi-tech security threats.
Improve processing efficiency of cyber threat event
High-Risk Focused Analysis
Expand processing range and reduce time via real-time incident event automatic analysis
Efficient allocation of resources
Unknown threats appear on the surface
Provide preemptive response system
Share collected information related to organization
Collect domestic/foreign threat intelligence and newest information of malicious codes
Preemptive response to similar threat
Improve cyber security management efficiency
Create an asset information vulnerability self assessment system
Shorten vulnerability detection time
Vulnerability updates through continued inspection
Automatized alert event processing through supervised learning
The SPiDER TM AI Edition is capable of increasing alert event processing efficiency and preemptively responding to threats through supervised learning of various scenarios.
It is capable of predicting threat levels of alert events by creating and learning data according to attack patterns. The analysis results are also continuously upgraded through feedback from analytics.
Unknown threat detections by unsupervised learning
The SPiDER TM AI Edition is capable of detecting unknown threats by utilizing scenario based and user activity based data learning of each attack scenario.
It puts together then detects security logs and anomaly detections of alert events along with threat level prediction and is continuously upgraded through feedback from analytics.
This solution utilizes AI technology to optimize the work of the security control officer. By automating the analysis of massive security events newly generated every day, it increases the efficiency of security work. By selecting high-risk events that need to be addressed first, it reduces the time required to analyze vast amounts of security data. As a result, it enables faster response. The accuracy of prediction can be improved by repeating the process of generating training data to be applied to the AI algorithm and giving feedback on the results to the AI system.