Secure NFV Orchestration Over an SDN-Controlled Optical Network With Time-Shared Quantum Key Distribution Resources

Aguado, Alejandro; Hugues-Salas, E.; Haigh, Paul Anthony; Marhuenda, Jaume; Price, Alasdair B.; Sibson, Philip; Kennard, Jake; Erven, Chris; Rarity, John; Thompson, Mark G.; Lord, Andrew; Nejabati, Reza; Simeonidou, Dimitra

doi:10.1109/jlt.2016.2646921

Cited by 66 publications

(36 citation statements)

References 4 publications

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“…The SDN controller is capable of realizing flexible and programmable global optical network management, which can be utilized as the effective implementation technique for control layer. Moreover, it has been demonstrated in the recent study on time-shared QKD resources in SDN-controlled optical networks [28].…”

Section: An Example Of Qkp For Secret Key Provisioning Between Node-amentioning

confidence: 94%

Quantum Key Distribution (QKD) over Software-Defined Optical Networks

Zhao¹,

Cao²,

Yu³

et al. 2019

Quantum Cryptography in Advanced Networks

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Optical network security is attracting increasing research interest. Currently, software-defined optical network (SDON) has been proposed to increase network intelligence (e.g., flexibility and programmability) which is gradually moving toward industrialization. However, a variety of new threats are emerging in SDONs. Data encryption is an effective way to secure communications in SDONs. However, classical key distribution methods based on the mathematical complexity will suffer from increasing computational power and attack algorithms in the near future. Noticeably, quantum key distribution (QKD) is now being considered as a secure mechanism to provision information-theoretically secure secret keys for data encryption, which is a potential technique to protect communications from security attacks in SDONs. This chapter introduces the basic principles and enabling technologies of QKD. Based on the QKD enabling technologies, an architecture of QKD over SDONs is presented. Resource allocation problem is elaborated in detail and is classified into wavelength allocation, time-slot allocation, and secret key allocation problems in QKD over SDONs. Some open issues and challenges such as survivability, cost optimization, and key on demand (KoD) for QKD over SDONs are discussed.

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Section: An Example Of Qkp For Secret Key Provisioning Between Node-amentioning

confidence: 94%

Quantum Key Distribution (QKD) over Software-Defined Optical Networks

Zhao¹,

Cao²,

Yu³

et al. 2019

Quantum Cryptography in Advanced Networks

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“…These SDN functionalities are the key motivator for the integration of QKD in an SDN-enabled optical network, as shown in [15,16,17,18,19,20,21]. The current works have proved that the SDN integration is beneficial for the QKD networks for customized network configuration (e.g.…”

Section: Monitoring and Physical Layer Attack Mitigation In Sdn-contrmentioning

confidence: 97%

Monitoring and Physical-Layer Attack Mitigation in SDN-Controlled Quantum Key Distribution Networks

Hugues-Salas

Ntavou

Gkounis

et al. 2019

J. Opt. Commun. Netw.

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Quantum Key Distribution (QKD) has been identified as a secure method for providing symmetric keys between two parties based on the fundamental laws of quantum physics, making impossible for a third party to copy the quantum states exchanged without being detected by the sender (Alice) and receiver (BoB) and without altering the original states. However, when QKD is applied in a deployed optical network, physical layer intrusions may occur in the optical links by injecting harmful signals directly into the optical fibre. This can have a detrimental effect on the key distribution and eventually lead to its disruption. On the other hand, network architectures with software defined networking (SDN) benefit from a homogeneous and unified control plane that can seamlessly control a QKD enabled optical network end-to-end. There is no need for a separate QKD control, a separate control for each segment of an optical network and an orchestrator to coordinate between these parts. Furthermore, SDN allows customised and application tailored control and algorithm provisioning, such as QKD aware optical path computation, to be deployed in the network, independent of the underlying infrastructure. Therefore, in this manuscript, we investigate the integration of the application, SDN and QKD infrastructure layers and confirm capability for flexible supervision and uninterrupted key service provisioning in the event of link level attacks. An experimental demonstrator is used, for the first time, to verify the architecture proposed, considering realtime monitoring of quantum parameters and fiberoptic link intruders to emulate real-world conditions. Furthermore, attacks on a standard single-mode fiber (via a 3dB coupler) and a multicore fiber (via an adjacent core) are undertaken to explore different connectivity between QKD units. Results show an additional attacker identification and switching time of less than 60ms for the link cases investigated, being negligible compared to the total (re)initialization time of 14 minutes of the QKD units.

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“…SDN holds a programmable and flexible centralized control manner to provide efficient and easy management for QKD networks. In [48], it was demonstrated that SDN can reduce costs in a QKD network for time-sharing of the available resources. In [49], SDN was introduced in a QKD network to provide real-time monitoring of quantum parameters, e.g., secret-key rate and quantum bit error rate.…”

Section: B Qkd Network Managementmentioning

confidence: 99%

Multi-Tenant Provisioning for Quantum Key Distribution Networks With Heuristics and Reinforcement Learning: A Comparative Study

Cao

Zhao

et al. 2020

IEEE Trans. Netw. Serv. Manage.

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Quantum key distribution (QKD) networks are potential to be widely deployed in the immediate future to provide long-term security for data communications. Given the high price and complexity, multi-tenancy has become a cost-effective pattern for QKD network operations. In this work, we concentrate on addressing the online multi-tenant provisioning (On-MTP) problem for QKD networks, where multiple tenant requests (TRs) arrive dynamically. On-MTP involves scheduling multiple TRs and assigning non-reusable secret keys derived from a QKD network to multiple TRs, where each TR can be regarded as a high-security-demand organization with the dedicated secret-key demand. The quantum key pools (QKPs) are constructed over QKD network infrastructure to improve management efficiency for secret keys. We model the secret-key resources for QKPs and the secret-key demands of TRs using distinct images. To realize efficient On-MTP, we perform a comparative study of heuristics and reinforcement learning (RL) based On-MTP solutions, where three heuristics (i.e., random, fit, and best-fit based On-MTP algorithms) are presented and a RL framework is introduced to realize automatic training of an On-MTP algorithm. The comparative results indicate that with sufficient training iterations the RL-based On-MTP algorithm significantly outperforms the presented heuristics in terms of tenant-request blocking probability and secret-key resource utilization.Index Terms-Quantum key distribution networks, online multi-tenant provisioning, heuristics, reinforcement learning.

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Secure NFV Orchestration Over an SDN-Controlled Optical Network With Time-Shared Quantum Key Distribution Resources

Abstract: We demonstrate, for the first time, a secure optical network architecture that combines NFV orchestration and SDN control with quantum key distribution (QKD) technology. A novel time-shared QKD network design is presented as a cost-effective solution for practical networks.

Cited by 66 publications

References 4 publications

Quantum Key Distribution (QKD) over Software-Defined Optical Networks

Quantum Key Distribution (QKD) over Software-Defined Optical Networks

Monitoring and Physical-Layer Attack Mitigation in SDN-Controlled Quantum Key Distribution Networks

Multi-Tenant Provisioning for Quantum Key Distribution Networks With Heuristics and Reinforcement Learning: A Comparative Study

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