Five Behavioral Detection Engines of FFRI yarai

Legacy Security Technology Cannot Prevent Sophisticated Cyber Crimes Anymore

To prevent “unknown threats” used for recent cybercrimes, we need to “think ahead of attackers” by:

  • - Capturing the “cause” leading to the crimes
  • - Predicting the attack techniques that could be used in the future
  • - Developing the solution to prevent the threats

Precognitive Defense Supported by Five Behavioral Detection Engines

FFRI Security’s unique detection technology using 5 detection engines proactively blocks virus attacks.

Protecting Applications From Vulnerability Attacks

ZDP Engine

Protecting From Attacks Targeting Software Vulnerabilities

Protects against virus attacks that target known and unknown vulnerabilities such as attacks when viewing emails or Web pages. Protects against arbitrary code execution attacks by use of our original API-NX technology (Patent No. 4572259).

Detecting Unknown And Known Virus

Static Analysis Engine

Analyzing Structure And Characteristics Of Program Before Execution

Analysis performed without executing a program. Detection is performed by using N-Static Analysis that incorporates numerous analysis methods including PE Structure Analysis, Linker Analysis, Packer Analysis, and Speculative Operation Analysis.

HIPS Engine

Monitoring Behaviors Of A Program To Immediately Block Malicious Activities

Monitors the behavior of currently running programs. Our unique D-HIPS Logic detects behavior such as program intrusion, unusual network access, keylogger and backdoor access behavior.

Sandbox Engine

Evaluating A Program In A Virtual Environment Without Impacting A System

Runs programs in a virtual environment that includes a virtual CPU, virtual memory and virtual Windows subsystems. Detection is based on a combination of commands based from our unique U-Sandbox Detection Logic.

Machine Learning Engine

Blocking Behaviors With Malicious Characteristics Based On Big Data Analysis

Monitors running programs based on big data related to malware that has been captured by FFRI Security. Behavioral characteristics in big data are then extracted to detect malicious behavior in systems by using machine learning to analyze such characteristics.

Precognitive Defense

powered by FIVE core protection engines

FFRI Security is committed to research and development of preventing the most advanced cyber-attacks and breaches.

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