Protecting the modern information and industrial environment, the internet of things (IoT), and the industrial internet of things (IIoT) is a task that cannot be accomplished without the use of machine-learning technologies. Although modern technologies, including neural network-based deep learning, have taken big data processing to a new level, numerous technological barriers still need to be addressed. For instance, memory organization in neural networks and contextual processing of information are two issues that have yet to be completely resolved. And in the IoT era, the energy performance of computing devices is becoming increasingly important.
Our research team is working on these and other issues with a view to security.
Among the projects we have implemented is Kaspersky MLAD, a system for early detection of anomalies across a broad spectrum of technological processes.
Kaspersky MLAD ensures the security of cyber-physical systems (ICS, IoT, and IIoT) based on the detection and interpretation of anomalies using machine-learning techniques in the telemetry of technological processes.
IoT security is one of the most pressing issues in the contemporary world. The number of devices is growing so rapidly that their behavior requires additional control. With that in mind, we are developing an ML engine to detect abnormal behavior by smart things and to warn their owners about it. Among its key elements, our approach involves creating a behavioral profile of the device and processing data in close proximity to its location so as to reduce the amount of traffic transmitted to the cloud (so-called edge computing).
A machine-learning technology based on neuromorphism, featuring solutions that use spiking neural networks (SNN) and cognitive technologies.
Our team is made up of experts with many years of scientific experience, talented young researchers, candidates and doctors of science in the fields of machine learning and mathematics, experienced programmers, engineers, and IT specialists.
We are open to cooperation in these and related technological and scientific disciplines.