ATENA H2020 Workshop – October 18, 2018, 9:00-17:30

A new cybersecurity for interdependent Critical Infrastructures

Under the patronage of the Minister of the Economy and Foreign Trade Étienne Schneider

Targeted at managers willing to use innovative cybersecurity techniques to protect their critical assets, mainly critical infrastructure such as electricity, gas, water distribution system or transport systems, but also other critical ICT systems.

When: Thursday – October 18, 2018, 9:00-17:30

Organized by: the University of Luxembourg in partnership with itrust consulting sàrl

Location: Maison des Arts et des Étudiants (MAE), 6, avenue de la Fonte, L-4364 Esch-zur-Alzette

Agenda (reduced):
09:00 – 09:30 Welcome and Registration
09:30 – 11:00 Security of the Grid and the ATENA Approach
11:15 – 13:00 ATENA innovations: the theoretical approach
14:00 – 15:10 ATENA innovations: the practical approach
15:10 – 15:30 Other research projects on Critical Infrastructure Protection
15:30 – 16:30 Panel Discussion
17:00 – 21:30 Cybersecurity week

Privacy Statement updated

itrust consulting s.à r.l. has updated its Privacy Statement.

Doctoral degree awarded to Steve Muller of itrust consulting sàrl

On 26 June Steve Muller of itrust consulting defended his PhD thesis in Computer Science on Risk Monitoring and Intrusion Detection for Industrial Control System (ICS) at the University of Luxembourg.

itrust consulting participates in QUARTZ on satellite-based key distribution

itrust consulting s.à r.l. is proud to announce that it has recently signed a contract with SES to participate as one of the many project partners in the recently publicized QUARTZ consortium (https://www.ses.com/press-release/esa-and-ses-led-consortium-develop-satellite-based-cybersecurity), primarily funded by the European Space Agency (ESA) via its ARTES/ScyLight programme.

Please select the Links below to read the full press release and to access further project details as published by SES and ESA.

itrust consulting publishes an article on Training-Resistant Anomaly Detection Systems

Modern network intrusion detection systems rely on machine learning techniques to detect traffic anomalies and thus intruders. However, the ability to learn the network behaviour in real-time comes at a cost: malicious software can interfere with the learning process, and teach the intrusion detection system to accept dangerous traffic.
The recently published article presents an intrusion detection system (IDS) that is able to detect common network attacks including but not limited to, denial-of-service, bot nets, intrusions, and network scans.
With the help of the proposed example IDS, it is shown to what extent the training attack, and more sophisticated variants of it, have an impact on machine-learning based detection schemes. The analysis is then used to design an intrusion detection system that is resilient to such kind of attacks.