Business Requirements Questionnaire
Dear Participant,

We kindly seek your response to this survey. The purpose of this survey is to define the user, stakeholder, security and privacy requirements from the business perspective for the ongoing H2020 project. INSPIRE-5Gplus aims at providing and demonstrating a smart, trustworthy and liability-aware 5G security platform for future connected systems. Briefly, the project is built around the following objectives:

- A conceptual architecture for supporting zero-touch end-to-end smart network and service security management in 5G and beyond networks. The architecture will leverage on flexibility of softwarization technologies (e.g., SDN/NFV) and smartness of AI/ML techniques;
- Software-defined security (SD-SEC) orchestration and management that enforces and controls security policies in real-time and adapt to dynamic changes in threats landscape and security requirements in 5G and beyond networks;
- Novel AI-driven security models, including AI-empowered Moving Target Defence (MTD) mechanisms and AI-driven Cyber Threat Intelligence (CTI) framework to empower smart security management with proactive defensive posture. The use of distributed and cooperative AI/ML models will be fostered to improve the prediction and detection accuracy as well as latency of AI-driven security models;
- Advanced mechanisms to foster trustworthiness of smart SD-SEC solutions in a multi-tenant/multi- domain setting by empowering trust in software components (e.g., VNFs) and AI/ML techniques. Trust in software components will be based on Trusted Execution Environments (TEEs), new Digital Rights Management (DRM) approaches, novel AI-powered validation tools, and a new labelling scheme. Trust in AI/ML models will rely on interpretability, adversarial machine learning, and blockchain;
- New mechanisms to enforce liability of involved parties when security breaches occur and/or system fail, including smart contracts and potentially VNF package Manifest to define Trust Level Agreement (TLA), mechanisms to enable AI liability, and new Root Cause Analysis (RCA) techniques.
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