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IGLOO SECURITY, INC. acquires 3 patents related to artificial intelligence and security monitoring

2022.06.03

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IGLOO SECURITY, INC. acquires 3 patents related to artificial intelligence and security monitoring



–acquires 3 patents related to artificial intelligence and security monitoring …Focusing on simplify the security monitoring work process from threat detection to response

 

[20th/May/2020] Igloo Security Co., Ltd. (CEO Lee Deuk-Choon, www.igloosec.co.kr) said, 'Monitoring device and program on how to generate response instructions and analyze application results (Registration No. 10-2111136 ),'Unsupervised learning-based anomaly detection method and its system (Registration No. 10-2110480)' and 'Machine learning-based frequency security policy generation system and its method (Registration No. 10-2108960)' patents registration was completed. Igloo Security plans to apply three patented technologies to SPiDER TM AI Edition, an AI security monitoring solution.

 

Igloo Security's three patents aim to shorten the process from threat detection to response based on accurate analysis of cyber attacks that evolve every day. Through the application of the patents registered this time, it is expected to respond in a timely manner to infringement incidents that may affect major IT systems and to increase the efficiency of security control.

Patents on 'Methods for generating response instructions and analyzing application results, monitoring devices, and programs' rank high-risk events that need to be responded first through simulation from a security and operational perspective, and respond with appropriate response times and response methods The focus is on generating instructions. By matching the threat information analyzed through the simulation module with the asset information, and predicting the damage size and recovery cost, and generating a response instruction based on this, it is possible to respond more promptly to attack events that may cause significant damage.

 

The patent for 'Unsupervised learning-based anomaly detection method and system' learns the prediction model by learning the feedback data provided by security experts about incorrect predictions among the prediction results produced by the deep neural network-based machine learning model through unsupervised learning. In the process of improving, the focus is on supplementing the problem of bias due to the loss of part of the information learned from the past data. Through the technology that selects useful parts of the feedback data and continuously trains the model using it, the learning efficiency of the machine learning model can be improved.

 

The patent for ‘machine learning based frequency type security policy generation system and method’ is a technology that creates a security policy that reflects the frequency of infringement threats identified through machine learning and its risk and automatically applies this policy to security device. By applying a security control policy that reflects changes in the attack flow in real time, it is possible to increase the visibility of security events that increase exponentially every day and minimize false positives that decrease the effectiveness of security monitoring tasks.

 

"The application of this patent technology is expected to shorten the process from threat detection to response and improve the effectiveness of security monitoring," said Lee Deuk-choon, CEO of igloo security. "As a leader in AI security monitoring, we will put more emphasis on the development of technology that can increase the response to advanced cyber infringement attempts."