Jürgen Neises

R&I Subsidies Program Manager, Fujitsu

Dr. Jürgen Neises is Senior Consultant and manages the Fujitsu Europe P&I Subsidies Program. Since 1990, he has led a number of research and innovation projects on infrastructure, mobile and security solutions in research and at Fujitsu. Jürgen's track record includes high-performance computing, carrier-grade availability, and a wide range of security solutions. Currently, Jürgen leads Fujitsu's participation of the Horizon 2020 project sSecureIoT (Grant No. 779899), FINSEC (Grant No. 786727) and INFINITECH (Grant No. 856632). Jürgen is Fujitsu Distinguished Engineer.

Jürgen is speaking at

Focus Track 2 - Technology, Platforms and Trust
November 5, 2020
11:00 am - 12:00 pm

Speakers

  • Spyros Evangelatos (Speaker) Senior Research & Innovation Specialist, INTRASOFT International
  • Daniel Calvo Alonso (Speaker) Head of AI, Data & Robotic unit, ATOS Research and Innovation
  • Jürgen Neises (Speaker) R&I Subsidies Program Manager, Fujitsu
  • Mariza Konidi (Parallel session chair) Research & Innovation Communication and Project Management Specialist, INTRASOFT International

Description

This session will serve to familiarize the audience with the SecureIoT solution and how data analytics and machine learning can assist in enhancing cybersecurity.

The objectives of this session are:

  • To reveal the power of data in terms of prediction of IoT systems behaviour.
  • To demonstrate cybersecurity solutions targeting IoT systems (Platforms, Applications) from the identification of trustworthy behavior of IoT devices to the establishment of secure IoT Services.
  • To facilitate compliance to cybersecurity and privacy regulations.
  • To convince the audience of the imminent application of data analytics as a cybersecurity solution for the future.

The IoT landscape is evolving to decentralized systems of systems implying multiplatform interactions and including powerful autonomous smart objects and embedded systems at the edge. This new reality is introducing challenging issues in terms of security and privacy as we have seen in recent attacks which may even imply safety concerns in critical domains. This presentation will cover the advances brought by SecureIoT project regarding the usage of Artificial Intelligence and data analytics to exploit information collected from the multiple levels of IoT systems in an efficient, non-intrusive and intelligent fashion. The outcomes of the Machine Learning models are being used to feed a set of security services that cover the requirements of multiple stakeholders: risk assessment, compliance auditing and support to developers. Predictive analytics will also be discussed as a valuable tool towards secure cyber-physical systems, especially covering three diverse domains such as autonomous vehicles, socially assistive robots and industry 4.0.



 

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