Technology made in Europe
Materna Radar Cyber Security’s technology is driven by the strong combination of human expertise and innovation in research and development.
Thanks to proven experts and state-of-the-art European security solutions, we can offer you the services you need today to continue to provide holistic cybersecurity in the future.
Our heart beats for European security solutions
We drive innovative in-house technology – without built-in back doors
We meet global challenges with European security awareness
More data means more risks. Thanks to the use of the latest technologies such as machine learning, threat intelligence, big data analytics and the experience and know-how of our experts from the Cyber Defense Center, we ensure that IT and OT early warning systems are always state of the art.
Everyone leaves traces…
Correlation within a module and cross-correlation of information from different modules lead to a high-quality detection of risks and security problems and a comprehensive view of the activities in the company.
In organizations, information is often available in silos and may therefore be neglected or underused. A correlation of logs with vulnerabilities, IDS data, Log Data Analytics findings and numerous other data provides a new type of general overview of security-relevant data.
Correlation and cross-correlation are based on rules, policies and self-learning algorithms: rules are predefined to recognize patterns. They are continuously expanded and tailored to the needs of the customer. Policies are used to determine whether specific actions are taking place at the right time and in the right place. Self-learning algorithms include the ability of the correlation engine to learn to distinguish between normal and abnormal occurrences and to be able to detect changes in behavior in applications, servers and other network areas. Use outside of business hours, excessive use of applications or other IT services and patterns of network traffic over time and compared to past periods (taking into account daily, weekly, monthly and seasonal fluctuations) are examples of abnormality detection.
The findings are analyzed by our cyber defense team. In a critical situation, security experts receive an immediate alert. In pre-defined, particularly critical situations, the customer also receives real-time alerts.
See data in context
Track all events in your infrastructure to identify malicious activity
Materna Radar Cyber Security tracks all events within your infrastructure and identifies malicious activities.
Using Big Data Analytics, Radar Analytics Interface (RAIN) gives companies a complete overview. It contextually combines incidents from multiple sources, live data as well as historical data, to give experts the complete picture to help to identify new incidents that could be related to others that occurred in the past.
Security intelligence
Coupled with internal and external security intelligence feeds that provide current information about the latest vulnerabilities, the identification of ongoing advanced cyberattacks on networks is facilitated.
The large amount of historical data simplifies the distinction between normal activity patterns of a particular network and anomalies. Data can come from a variety of historical risk sources and in combination with real-time data, experts gain a dynamic view for a proactive analysis of new and potentially harmful data types, which enable the discovery of unknown patterns and offer a new level of knowledge.
Big Data Analytics is part of a successful cyber security strategy. But it is only effective if it is executed correctly. For this reason, RAIN relies on our threat intelligence and machine learning so that companies can concentrate on serious threats and to ensure the security of companies in the future.
You’ve got to know what’s coming
Eradicate threats before they happen
Proactive defense and mitigations are important for companies. Materna Radar Cyber Security’s Threat Intelligence is used to enhance cyber security efforts. It provides insights into future business risks and so far unknown threats. This improves decision making and reduces business risks. Overall it is an upgrade for the effectiveness of early detection and clearly focuses on a proactive cybersecurity approach.
Know how, know when, know who
Materna Radar Cyber Security’s Threat Intelligence is based on various internal and external feeds as well as a collection of reports covering a wide range of unknown threat information. These feeds are used in conjunction with Our security detection modules such as Log Data Analytics add extra value, advantage and effectiveness.
Materna Radar Cyber Security’s Threat Intelligence helps companies to manage the information overload relating to IT security by filtering the most relevant details and key facts for organizations.
Work smarter and better
Materna Radar Cyber Security uses machine learning to analyze the increasing data volume, which makes our modules even more powerful. This state-of-the-art approach uses various algorithms and techniques to find and amplify patterns. Machine learning works best with larger data sets, which enables modules to collect and store more information about events. Machine learning enables a faster detection of incidents and cybersecurity professionals can focus on critical threats.
Machine Learning in a nutshell
Materna Radar Cyber Security uses machine learning to:
- analyze network threats
- detect malware
- detect threats
- support cyber security analysts
Machine Learning uses threat intelligence from feeds, internal network traffic and data analysis. Real-time data is tracked and correlated to provide a more comprehensive view of the threat landscape. This information is used to identify, correlate, track and prepare for risks at an early stage. Machine Learning connects data sets to adapt to rapidly changing risk environments and trends. One incident can improve the intelligence of the entire system.
Tightening data networks
The sheer volume of data has grown significantly over the years. Machine learning automates repetitive tasks and networks all data sets. It takes over the complex enrichment of data. This allows Materna Radar Cyber Security’s security detection modules to adapt quickly to changing environments and trends. The detection of an abnormality can improve the intelligence of the entire system.
