In this era of virtualisation, the abstraction of underlying hardware resources and the prominence of tools for infrastructural automation have been key enablers for the deployment of distributed services at scale. The growing role of software in managing infrastructures and the DevOps movement, focused on the automation of infrastructure management, are targeting the challenges of increasing speed and quality of infrastructure management, thus lowering costs and enhancing security and trustworthiness. However, the market of infrastructure automation tools is fragmented, there is no single one to manage the whole lifecycle of infrastructure as code (IaC) and existing solutions do not address all trustworthiness and security aspects throughout the whole lifecycle. PIACERE will develop tools, techniques and methods enabling organisations to fully embrace the IaC approach through the DevSecOps philosophy. PIACERE will provide the first Integrated Development Environment (IDE) to develop and verify IaC. Exploiting Model-Driven Engineering (MDE), the IDE will enable developers to create infrastructural code at an abstract level. Using the novel DevOps Modelling Language (DOML), the DevOps team will generate IaC for different languages and verify its correctness at model and code level along with the corresponding security components. The IDE is one part of the complete workflow and will be supported with: 1) a canary environment to aid the simulation of the conditions of the production environment allowing the early identification of potential vulnerabilities and 2) an IaC execution Environment to automatically deploy, monitor and ensure that the conditions are met, incorporating self-healing and self-learning features. The integration, security first and IaC polyglotism arm the DevSecOps teams to treat and work with IaC as they do with traditional code, simplifying the design, development and operation of IaC, while increasing their productivity, quality and reliability

The advent of Social Networks has made both companies and public bodies tremendously exposed to the so-called Social Engineering 2.0, and thus prone to targeted cyber-attacks. Unfortunately, there is currently no solution available on the market that allows neither the comprehensive assessment of Social Vulnerabilities nor the management and reduction of the associated risk. DOGANA aims to fill this gap by developing a framework that delivers "aDvanced sOcial enGineering And vulNerability Assessment". The underlying concept of DOGANA is that Social Vulnerabilities Assessments (SVAs), when regularly performed with the help of an efficient framework, help deploy effective mitigation strategies and lead to reducing the risk created by modern Social Engineering 2.0 attack techniques. Two relevant features of the proposed framework are: i) the presence of the "awareness" component within the framework as the cornerstone of the mitigation activities; ii) the legal compliance by design of the whole framework, that will be ensured by a partner and a work package explicitly devoted to this task. Moreover, the outcomes of the project are also expected to provide a solid basis to revise the insurance models for cyber-attacks related risks, thanks to the involvement of 2 strong DOGANA partners in this area of activity. The project will be implemented by a consortium of 18 partners, from 11 different countries, including users, technology providers of whom 3 are major world-wide cyber-security solutions market leaders as well as legal and psychological expertise. An extensive field trial plan enables the testing of the DOGANA platform with six users (4 partners and 2 supporting users) operating in the critical areas of energy, finance, transport, utilities, and public authorities. DOGANA has also created a unique consortium with a world-wide scope.

Artificial Intelligence has become a major innovative force and it is one of the pillars of the fourth industrial revolution. This trend has been acknowledged also by the European Commission that has already pointed out how high-performance, intelligent, and secure networks are fundamental for the development and evolution of the multi-service Next Generation Internet (NGI). While great progress has been done during the last years with respect to the accuracy and performance of AI-enabled platforms, their integration in potentially autonomous decision-making systems or even critical infrastructures requires end-to-end quality assurance. AI@EDGE addresses the challenges harnessing the concept of “reusable, secure, and trustworthy AI for network automation”. In AI@EDGE European industries, academics and innovative SMEs commit to achieve an EU-wide impact on industry-relevant aspects of the AI-for-networks and networks-for-AI paradigms in beyond 5G systems. Cooperative perception for vehicular networks, secure, multi-stakeholder AI for IIoT, aerial infrastructure inspections, and in-flight entertainment are the uses cases targeted by AI@EDGE to maximise the commercial, societal, and environmental impact. To achieve the goal, AI@EDGE targets significant breakthroughs in two fields: (i) general-purpose frameworks for closed-loop network automation capable of supporting flexible and programmable pipelines for the creation, utilization, and adaptation of the secure, reusable, and trustworthy AI/ML models; and (ii) converged connect-compute platform for creating and managing resilient, elastic, and secure end-to-end slices capable of supporting a diverse range of AI-enabled network applications.

Recent trends in industrial technology and the adaptation of Industrial Internet of Things (ΙIοΤ), has emerged by the convergence of Operations Technology (i.e., traditional hardware and software systems) and Information Technology (i.e., advanced computing, data aggregation/analysis, and ubiquitous communication systems). IIoT has great potential to enable significant advances in optimizing operations among large number of increasingly autonomous control systems and devices, and can have a profound impact on many industry domains, where smart factories and logistics are among most notable cases. However, a major barrier towards IIoT adoption lies in cybersecurity issues that makes it extremely difficult to harness its full potential: IIoT systems dramatically increase the attack surface (introducing new security threats due to newly connected devices and protocols, making them more vulnerable to interference), the disruption of process controls, the theft of intellectual property, the loss of corporate data, and the industrial espionage. C4IIoT will build and demonstrate a novel and unified IIoT cybersecurity framework for malicious and anomalous behavior anticipation, detection, mitigation, and end-user informing. The framework provides a holistic and disruptive security-enabling solution for minimizing attack surfaces in IIoT systems, by exploiting i) emerging security software and hardware protection mechanisms; ii) state of the art machine and deep learning and privacy-aware analytics; iii) novel encrypted network flow analysis; iv) secure-by-design IIoT device fabrication; and v) blockchain technologies, to provide a viable scheme for enabling security and accountability, preserving privacy, enabling reliability and assuring trustworthiness within IIoT applications. The C4IIoT framework will be demonstrated and validated on two carefully selected use cases in real world environments, namely Enabling security IIoT in i) Inbound Logistics and ii) a Smart Factory