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 to various technological advancement such as the vast amounts of IT infrastructure, explosive increase in data, complex compliances, tightening legal regulations. 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.


  • 1

    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

    Collect the latest domestic and foreign threat information and malicious code

  • 2

    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

  • 3

    Improve cyber security management efficiency

    Create an asset information vulnerability self assessment system

    Systemize, diagnose and organize IT assets

    Vulnerability updates through continued inspection

Key Features

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 behavior 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.

System Structure

Introduction Effect

This solution utilizes AI technology to optimize the work of the security monitoring 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.

Monitoring service innovation by improving security monitoring productivity and minimizing threats