MENDEL is based on 10 years of extensive academic and industrial research, designed using the same technology, which was successful in multiple NIST Challenges. It’s Data Analysis and Anomaly Detection engine learns the behavioral patterns in the network to detect both known and unknown attacks from outside and inside, including data leaks, operational anomalies, and Advanced and Persistent Threats invisible to other security technologies.

Our research interests lie in cybersecurity for IT and OT networks as SCADA, IoT, industrial, medical, transport, and wireless technologies that don’t have an End-Point Protection (antivirus); focusing on techniques of Machine Learning and especially Anomaly Detection.

GREYCORTEX partners with leading research institutions worldwide in the fields of artificial intelligence, machine learning, and cybersecurity for both IT and Industrial environments. Our current research projects are below.

Interested in working with us?

Click “Contact Research” to get in touch with our Research Department.

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Advanced behavioural models of application layer for effective analysis of traffic in business networks

Funded by the Technology Agency of the Czech Republic within the ZETA Programme

The MENDEL Content-based Analysis module uses multiple methods of artificial intelligence, machine learning, and advanced analysis to detect malicious, suspicious, and anomalous transactions on the Application Layer (OSI layer 7 — HTTP and SMB) in enterprise networks. The module autonomously learns the common behavior of defined applications and their users, and reports the anomalies, attacks, and other advanced threats to the MENDEL user.

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Monitoring and analysis of communication for security surveillance
of critical energy infrastructure

Funded by the Ministry of the Interior of the Czech Republic

The project focuses on industrial research of a comprehensive system to protect critical energy infrastructure from cyber security threats using advanced power grid monitoring and advanced artificial intelligence algorithms.

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Advanced methods for wireless traffic monitoring

Funded by the Technology Agency of the Czech Republic within the ZETA Programme

The project Advanced Methods of Monitoring the Operation of Wireless Networks focused on research and development in the field of intelligent analysis of wireless network operations based on the communication standards of the IEEE 802.11 family. The goal, together with Brno University of Technology, was to develop a solution providing advanced continuous monitoring of wireless traffic and early detection of current and future operational and cyber (information) security threats and incidents in wireless networks. 

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Data Monitoring to Increase the Reliability of Smart Factory Processes

Funded by Ministry of Industry and Trade of the Czech Republic within the TRIO Programme

The goal of the project is to research and develop a comprehensive system of monitoring and analytical methods to increase the safety, security, reliability and efficiency of automated production processes. In particular, the project is situated into safe and reliable intelligent manufacturing
systems within the framework of Smart Factory, Industrial Internet of Things and Industry 4.0 using advanced process, communication and sensor technologies. 

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