A study found that unplanned downtime – be it due to an equipment failure or cyber incident – is costing industrial manufacturers an estimated $50 billion each year. Unfortunately, it is often difficult to catch the issues that cause such disruption before they occur. Kaspersky MLAD has been designed to combat these costly problems early and help manufacturers significantly reduce their impact, by using ML algorithms that analyze telemetry from machinery sensors in real time and provide the operator with a graphical interface showing the analysis of detected anomalies.
Kaspersky Machine Learning for Anomaly Detection was shortlisted for this award for the first time. Along with Kaspersky MLAD the ‘Safety and Security’ category shortlist included eight nominees providing solutions from such areas as software protection and licensing, cyberthreat investigation and forensic, and safety monitoring, as well as firewalls, input modules and emergency stop switches.
In addition to receiving the Computer & Automation Magazine award, Kaspersky MLAD also acquired a patent in the US for the first time in November 2021, which is another testament of the innovation this product brings to the market. The patented method allows early determination of anomalies in cyber-physical systems using a graphical user interface (GUI). Being granted the patent not only shows the uniqueness of Kaspersky MLAD but proves that this was a necessary invention for several different industries.
“We’re immensely proud of our product, and grateful for the recognition and trust awarded to us by our customers and the editorial team and readers at Computer & Automation Magazine. We will continue to enhance the various components of Kaspersky MLAD to adapt to users’ demands. In line with use cases we encounter in the industry, we will provide our customers with the best possible protection for their industrial facilities,” says Andrey Lavrentyev, Head of Technology Research Development, Kaspersky.
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