Kaspersky program to help universities and laboratories advance industrial cybersecurity research

Kaspersky has launched a dedicated collaboration program to help institutions become better equipped at understanding the latest and most prevalent industrial cybersecurity threats. By joining the program, educational institutions, laboratories, research departments, security operations centers (SOC) and emergency response teams (CERT and CSIRT) that meet the partner profile criteria will be able to improve how they conduct their research and train cybersecurity specialists using the Kaspersky Industrial CyberSecurity solution for free.

Industrial organisations keep facing the challenge of how to defend their industrial control systems (ICS) from a wide range of attacks. For instance, Kaspersky’s solutions helped to block malicious objects on nearly half (46%) of ICS computers worldwide in 2019. With this in mind, laboratories and institutions are constantly working to create methods that reduce the risks to industrial processes and systems and develop requirements for safe industrial processes. By closely collaborating with vendors, researchers who embrace dedicated security solutions can yield better results and foster the capabilities industrial organisations need to detect and defend themselves against the latest cyberthreats.

The data is obtained using the distributed antivirus network Kaspersky Security Network (KSN) and received from those KSN users who voluntarily agreed to have data anonymously transferred from their computers and processed for the purpose described in the KSN Agreement for the Kaspersky product installed on their computer.

The new program offers research institutions and facilities the opportunity to use Kaspersky’s core industrial cybersecurity tools and expertise to support them in achieving their research, development and educational goals. The technologies can be used to develop and test cybersecurity practices, analyse attacks and their impact on industrial systems, develop educational programs and improve knowledge of OT (operational technology) and cybersecurity professionals, and develop cybersecurity policies and ICS standards. To join the program, organisations should meet the partner profile criteria, such as being able to organise industrial process modeling testbeds, having educational or research programs on industrial cybersecurity and dedicated experts for laboratory development and maintenance.

The offering includes Kaspersky Industrial CyberSecurity and Kaspersky Machine Learning for Anomaly Detection solutions, as well as support with deployment and configuration. The Kaspersky Industrial CyberSecurity solution allows organisations to use applications for operator workstations, human-machine interfaces and ICS/SCADA server protection, as well as detecting industrial network attacks. Kaspersky Machine Learning for Anomaly Detection will enable detection, visualisation and interception of anomalies in industrial telemetry at a very early stage.

“As industrial processes become more complex and nuanced, so too do cyberthreats. Organisations are developing their systems at great speed, so keeping them protected is essential to achieving sustainable success. This new dedicated program from Kaspersky is not just about giving research laboratories the tools they need to detect threats, but also sharing our decades of expertise so institutions can upskill and train their researchers to become cybersecurity specialists. This ensures that cybersecurity solution-based knowledge, machine learning and human expertise can work in harmony and help keep industrial organisations protected from advanced and targeted cyberattacks,” comments Anton Shipulin, Solution Business Lead, Kaspersky Industrial CyberSecurity at Kaspersky.

Kaspersky has already worked with a number of educational institutions, including the Gubkin Russian State University of Oil and Gas, the Savona Campus at the University of Genoa in Italy and Singapore University of Technology and Design, to help further their research.


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