Standard

The present document aims to:

• To identify potential security vulnerabilities of NFV and to determine whether they are new problems, or just existing problems in different guises.
• To provide a reference framework within which these vulnerabilities can be defined.

Out of scope: To list vulnerabilities that NFV suffers from that are no different from pre-existing vulnerabilities of networking and virtualisation technologies and are not altered by the virtualisation of network functions.
 
Intended audience: Security experts wanting to deploy NFV but needing to identify and solve potential security issues and then to attain security accreditation for systems.
 
Ultimate goal of the NFV Security Expert Group: Identify and propose solutions to any new vulnerabilities that result from the introduction of NFV. To enable checks for these vulnerabilities to be incorporated into processes for security accreditation of products based on NFV.

The present document specifies the interface requirements, the interfaces and the necessary information elements enabling the fault, configuration and information, performance, state and log management of NFV-MANO functional entities.
 
In addition, the present document also describes the framework to support the management of NFV-MANO functional entities.
 
The different aspects specified in the present document have been analysed firstly in ETSI GR NFV-IFA 021

The present document specifies the functional requirements, interfaces and operations to support the provision of network services across multiple administrative domains based on the interactions between NFVOs in different administrative domains (supported over the Or-Or reference point).
 
The present document also specifies the information elements exchanged over the specified interfaces.
 
The different aspects specified in the present document are derived from ETSI GR NFV-IFA 028.

The present document defines the requirements to interface the Security Control to NFV-MANO as described in ETSI GS NFV-SEC 013 and the LI Controller in ETSI GR NFV-SEC 011. The present document identifies the extensions to the NFV-MANO architecture related to security management and monitoring. Multiple trust domains are considered.

The present document defines a framework for use within ETSI NFV ISG to coordinate and promote public demonstrations of Proofs of Concept (PoC) illustrating key aspects of NFV.
 
The objective for the PoCs is to build commercial awareness and confidence and encourage development of an open ecosystem by integrating components from different players.
This framework outlines:

• rationale for NFV ISG PoCs;
• NFV ISG PoC process;
• format and criteria for NFV ISG PoC Proposals;
• NFV ISG PoC Report format and requirements.

This standard includes medical 2D and 3D data management such as storage, compression for transfer, regulation for wired or wireless transfer and search engine development for data retrieval.

The potential for organizations to capture value from Big Data improves every day as the pace of the Big Data revolution continues to increase, but the level of value captured by companies deploying Big Data initiatives has not been equivalent across all industries. Most companies are struggling to capture a small fraction of the available potential in Big Data initiatives. The healthcare and manufacturing industries, for example, have so far been less successful at taking advantage of data and analytics than other industries such as logistics and retail. Effective capture of value will likely require organizational investment in change management strategies that support transformation of the culture, and redesign of legacy processes. In some cases, the less-than-satisfying impacts of Big Data projects are not for lack of significant financial investments in new technology. It is common to find reports pointing to a shortage of technical talent as one of the largest barriers to undertaking projects, and this issue is expected to persist into the future. This volume explores the adoption of Big Data systems and barriers to adoption; factors in maturity of Big Data projects, organizations implementing those projects, and the Big Data technology market; considerations for implementation and modernization of Big Data systems; and, Big Data readiness.