The SECASSURED project is redefining how security assurance is integrated throughout the development and operation lifecycle of digital infrastructures. The project aims to strengthen software supply chains by introducing a data-driven, AI-empowered framework for assurance-driven security engineering that delivers continuous compliance, proactive threat management, and certifiable trustworthiness across the IoT-edge-cloud continuum.
SECASSURED
Security Assurance-driven AI-based Security Services for Trustworthy Security Engineering from Left-to-Right
The Concept
What is the SECASSURED Framework offering that’s different?
SECASSURED turns assurance into a continuous, intelligent process, delivering a data-driven, AI-powered, and continuously adaptive assurance ecosystem built around digital twins
Assurance-Driven Security Engineering
Security and compliance are integrated by design, evolving dynamically with system and regulatory changes.
Federated Digital Twins (SecDevTwin & SecOpsTwin)
Virtual, closed environments for secure development, testing, and operations—linking design-time assurance with real-time monitoring.
AI-Powered Security Services
A comprehensive catalogue of intelligent tools (for compliance interpretation, vulnerability repair, anomaly detection, and orchestration) powered by LLMs and human-centred AI.
Continuous Compliance & Trustworthiness
Automated alignment with EU cybersecurity, privacy, and AI regulations (GDPR, AI Act, ISO standards).
Scalable & Extensible Platform
Open APIs and modular architecture allow integration of new AI models, tools, and industry-specific solutions.
Human-Centred AI Approach
Blends expert knowledge with explainable AI to enhance decision-making and maintain transparency in automated assurance.
Use Cases
Proof of domain independence
Latest news
A mix of research updates, insights, and scientific publications
SECASSURED Research on AI-Assisted Vulnerability Detection Presented at IEEE CSR 2026
On 5. August, 2026 Merve Astekin, SINTEF presented the research paper "Context Guardian: LLM-Assisted Context-Aware Static Analysis for Vulnerability Detection" at the 2026 IEEE International Conference on Cyber Security and Resilience (IEEE CSR 2026), held in Lisbon, Portugal. The paper was presented as part of the Robust Defense and Static…
When AI Can Be Fooled – Robust Models as the Goal of Modern AI Projects
By Marvin Vogt, Fraunhofer FOKUS Whether it’s self-driving cars, malware detection, or text generation: neural networks have long since established themselves as a key technology for many innovative applications. However, it has become apparent that such machine learning systems are vulnerable to malicious actors. This article is intended to provide a…
SECASSURED at the TAROT Summer School 2026
The SECASSURED project was presented at the TAROT Summer School 2026, 13-17. July 2026, in Munich, bringing its innovative cybersecurity research to an audience of researchers, students, and industry professionals working on trustworthy, secure, and resilient communication systems. As part of the programme, Wissam Mallouli (Montimage) delivered a presentation entitled…
