Modeling NFV Deployment to Identify the Cross-Level Inconsistency Vulnerabilities

Thirunavukkarasu, Sudershan Lakshmanan; Zhang, Mengyuan; Oqaily, Alaa; Chawla, Gagandeep Singh; Wang, Lingyu; Pourzandi, Makan; Debbabi, Mourad

doi:10.1109/cloudcom.2019.00034

Cited by 7 publications

(2 citation statements)

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“…These properties simplify the management of network services and allow the automation of their life cycle. However, as some earlier studies [98], [117], [118] have shown, the multi-layer nature of NFV introduces inconsistencies issues between layers. For instance, consider a scenario where NFV Orchestrator sends configuration commands to other NFV components to deploy a network service.…”

Section: Gap Analysis and Future Research Directionsmentioning

confidence: 95%

“…Cross-layer verification is therefore crucial to operate network services in NFV environments. Such a verification approach may require details for mapping network services' states across the layers [98]. However, this mapping conflicts with the NFV philosophy that rests on the decoupling and independence of layers.…”

Section: Gap Analysis and Future Research Directionsmentioning

confidence: 99%

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Network Services Anomalies in NFV: Survey, Taxonomy, and Verification Methods

Zoure

Ahmed

Réveillère

2022

IEEE Trans. Netw. Serv. Manage.

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Network Function Virtualization (NFV) has emerged as a disruptive networking architecture whose galloping evolution is prompting enterprises to outsource network functions to the cloud and ultimately harvest the fruits of cloud computing, including elasticity, pay-as-you-go billing model, and on-demand services provisioning. However, many reluctant enterprises oppose the benefits of this outsourcing to their critical and pressing concerns about security, trust, and compliance. The latter anticipate possible security and QoS policy violations stemming from dishonest behaviors by cloud providers, attacks by co-resident competitors, misconfiguration by cloud administrators, or implementations flaws by NFV developers. As a result, migrating sensitive workloads to the cloud requires enterprises to first assess risks by gaining knowledge of possible network services' anomalies and second, to build trust in the cloud by designing effective mechanisms to detect such anomalies.This survey provides scrutiny of network services anomalies that may occur in the NFV environments. We first present a taxonomy of network service anomalies and analyze their negative impacts on critical service attributes, including security and performance. Second, we compare and classify the existing anomalies' verification mechanisms from the literature. Finally, we point out the literature gap and identify future research directions for anomalies verification in NFV.

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Section: Gap Analysis and Future Research Directionsmentioning

confidence: 95%

Section: Gap Analysis and Future Research Directionsmentioning

confidence: 99%