WP5 – Methods and Tools for Auditing complex systems

 Coordinated by
 CNR (M04-M30)

Objective

This work package will focus on the development of techniques, methods and tools supporting the audit activity in the BIECO framework. Auditing includes retrieval of data from the field, such as data regarding the usage mode of an ICT system subject to runtime adaptation through the delivery of software updates. The main goal is to provide ecosystem trustworthiness’s evaluation leveraging executable simulation environments and runtime monitoring facilities. The monitoring results aim to provide useful feedback for setting up the simulation environment.

This work package has the following objectives:

  1. Definition of the executable simulation models and of the parameters against which the behavior of the ICT systems and their interacting actors within an ecosystem is judged as being trustworthy or not.
  2. Definition of monitoring methodologies and tools detecting malicious behaviors of ICT systems and interacting actors within the ecosystems and assessing the validity of the simulation models.
  3. Developing monitoring tools able to validate through real-time data of systems sensors and actuators the validity of simulation decisions.

Deliverables

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...

Second F2F Meeting, Vienna

Second F2F Meeting, Vienna

The second BIECO F2F meeting held in Vienna from October 17-19, 2022, primarily aimed to discuss the BIECO project's current status, the use cases, and present an overview of the BIECO Framework. Additionally, the meeting focused on iterative improvements of the BIECO...

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...

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