WP4 – Development of Resilient Systems

 Coordinated by
IESE (M01-M36)

Objective

In this WP, tools and methods will be developed for supporting creation of resilient systems w.r.t security attacks and vulnerabilities. The scope is to develop systems that can cope with behavior disturbances caused by malicious attacks, that manifest into a loss of control and can bring a system into hazardous situations. A resilient system shall be able to compensate for interruptions and get back into a safe state in case of emergency situations caused by malicious attacks. In this regard the system shall be able to autonomously and automatically construct awareness of its security in a dynamic environment, to recognize critical situations and to identify the right operational mode for remaining into a secure and trusted operational state.

Concretely, this work package has the following objectives:

  1. To develop methods and tools that enable runtime evaluation of system operational state in dynamic environments.
  2. To enhance existing tools that can predict failure propagation caused by malicious attacks and support the transition of an ICT system into a resilient state. Prediction is performed in a simulated environment by counteracting the capabilities of the system under evaluation to detect that it is under evaluation.
  3. To develop methods that during runtime bring a system into a safe, trusted state, making it resilient to malicious attacks.

Deliverables

  • D4.1 Report on Self-checking of vulnerabilities and failures WP4 (7 – RESILTECH) Report Confidential, only for members of the consortium (including the Commission Services) M30
  • D4.2 Report on methods and tools for the failure prediction WP4 (2 – Fraunhofer) Report Confidential, only for members of the consortium (including the Commission Services) M24
  • D4.3 Report on Method development for resilient systems WP4 (2 – Fraunhofer) Report Confidential, only for members of the consortium (including the Commission Services) M30

Outcomes

MENTORS – Monitoring Environment for System of Systems

MENTORS - Monitoring Environment for System of Systems Authors: Antonello Calabrò, Said Daoudagh, Eda Marchetti Document type: Publication in Conference proceedings Publication: Proceedings of the 17th International Conference on Web Information Systems and...

GRADUATION: A GDPR-based Mutation Methodology

GRADUATION: A GDPR-based Mutation Methodology Authors: Said Daoudagh, Eda Marchetti Document type: Publication in Conference proceedings/Workshop Publisher: Quality of Information and Communications Technology. QUATIC 2021. Communications in Computer and Information...

Reliability and Robustness of machine learning in Smart Ecosystems

Reliability and Robustness of machine learning in Smart Ecosystems

Within the Smart digital Ecosystems (SES), the utilization of AI, and Machine Learning (ML) in particular, becomes increasingly prevalent scenarios designed for elevating the user experience of a system's functional performance. The BIECO approach on building trust in...

BIECO Project – Methodology for Security Evaluation

BIECO Project – Methodology for Security Evaluation

We happily announce that BIECO has been presented at @YavaConf 2022!  The session entitled "BIECO Project - Methodology for Security Evaluation" has been presented on Tuesday - September 27th, by Marcin Byra, @7bulls.com. The presentation is available here....

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