The coming advent of Quantum Computing promises to jeopardize current communications security, undermining the effectiveness of traditional public-key based cryptography. Different strategies (Post-Quantum or Quantum Cryptography) have been proposed to address this problem. Many techniques and algorithms based on quantum phenomena have been presented in recent years; the most relevant example is the introduction of Quantum Key Distribution (QKD). This approach allows to exchange cryptographic keys among parties and does not suffer from the development of quantum computation. Problems arise when this technique has to be deployed and combined with modern distributed infrastructures that heavily depend on cloud and virtualisation paradigms. This paper addresses this issue by presenting a new software stack that effortlessly introduces QKD in such environments and involves a simulation tool for Quantum Key Distribution. This software stack allows for agnostic integration, monitoring, and management of QKD, independent from a specific vendor or technology. Furthermore, a QKD simulator is presented, designed, and tested. This latter contribution is suitable as a low-level testing device, as an independent software module to check QKD protocols, and as a testbed to identify future practical enhancements.
The EU-funded PALANTIR project proposes a cybersecurity framework combining privacy assurance, data protection, incident detection and recovery aspects under the same platform. The project main focus is on cyber-resilience of SMEs and compliance with the relevant data privacy and protection regulations. The outcomes of the project will be validated in diverse application areas (eHealth, eCommerce, 5G-MEC) and will provide enterprises with security tools that will boost their resilience at a reasonable cost to protect their assets in the ever evolving cyber threat range.
The recent years have witnessed a growth in the number of users connected to computer networks, due mainly to megatrends such as Internet of Things (IoT), Industry 4.0, and Smart Grids. Simultaneously, service providers started offering vertical services related to a specific business case (e.g., automotive, banking, and e-health) requiring more and more scalability and flexibility for the infrastructures and their management. NFV and SDN technologies are a clear way forward to address these challenges even though they are still in their early stages. Security plays a central role in this scenario, mainly because it must follow the rapid evolution of computer networks and the growing number of devices. The main issue is to protect the end-user from the increasing threats, and for this reason, we propose in this paper a security framework compliant to the Security-as-a-Service paradigm. In order to implement this framework, we leverage NFV and SDN technologies, using a user-centered approach. This allows to customize the security service starting from user preferences. Another goal of our work is to highlight the main relevant challenges encountered in the design and implementation of our solution. In particular, we demonstrate how significant is to choose an efficient way to configure the Virtual Network Security Functions in terms of performance. Furthermore, we also address the nontrivial problem of Service Function Chaining in an NFV MANO platform and we show what are the main challenges with respect to this problem.
In recent years, the growing number of devices connected to the internet led network operators to continuously expand their own infrastructures. In order to simplify this scaling process, the research community is currently investigating the opportunity to move the complexity from a hardware to a software domain, through the introduction of a new paradigm, called Network Functions Virtualisation (NFV). It considers standard hardware platforms where many virtual instances are allocated to implement specific network services. However, despite the theoretical benefits, the mapping of the different virtual instances to the available physical resources represents a complex problem, difficult to be solved classically. The present work proposes a Quadratic Unconstrained Binary Optimisation (QUBO) formulation of this embedding process, exploring the implementation possibilities on D-Wave's Quantum Annealers. Many test cases, with realistic constraints, have been considered to validate and characterise the potential of the model, and the promising results achieved are discussed throughout the document. The technical discussion is enriched with comparisons of the results obtained through heuristic algorithms, highlighting the strengths and the limitations in the resolution of the QUBO formulation proposed on current quantum machines.
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