Project Description

OTIOT develops a system for monitoring and detecting threats in OT/IoT environments (Operational Technology/Internet of Things) that allows the automated detection of attack patterns and identification of compromised devices, as well as the possible automated recovery of filtered sensitive data.

During the project, a system for deploying a network of OT and IoT device sensors will be studied and developed, as well as other systems for gathering information on threats. Likewise, technologies based on Big Data will be developed for the mass storage and processing of data and algorithms for the extraction of intelligence from the information between threat actors and cybercriminal groups.

The OTIOT system, which will be validated at the Blueliv and Eurecat facilities, will allow the implementation of effective defensive strategies to overcome security challenges posed by the introduction of interconnected IoT and OT environments and will allow the expansion of the Blueliv product engine to process malware and malicious URLs.

The project, led by Blueliv, includes participation from Eurecat via IT-Security Technology Unit. Eurecat collaborates in the project in the application of systems based on artificial intelligence, as well as in the definition of new intelligence algorithms for the automation of security management, of vital need and importance against the risks inherent in present and the future OT/IoT systems.

General details

Project

OTIOT – System for monitoring and detect threats in IoT and OT environments.

Project reference

RTC-2017-6175-7

Programme and call for tender

Project financed by the MINISTRY OF SCIENCE, INNOVATION AND UNIVERSITIES and by the European Union, within the framework of the call Retos-Collaboration of the State Program of Research, Development and Innovation Oriented to the Challenges of Society, within the State Research Plan Scientific and Technical and Innovation 2013-2016, with the main objective of promoting technological development, innovation and quality research.

FEDER