Intent-Based Network Management Automation in 5G Networks
draft-jeong-nmrg-ibn-network-management-automation-01
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|---|---|---|---|
| Authors | Jaehoon Paul Jeong , Jeonghyeon Kim , Yongjun Noh , Younghan Kim | ||
| Last updated | 2023-04-24 (Latest revision 2022-10-24) | ||
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draft-jeong-nmrg-ibn-network-management-automation-01
Network Management Research Group J. Jeong, Ed.
Internet-Draft J. Kim
Intended status: Informational Y. Noh
Expires: 26 October 2023 Sungkyunkwan University
Y. Kim
Soongsil University
24 April 2023
Intent-Based Network Management Automation in 5G Networks
draft-jeong-nmrg-ibn-network-management-automation-01
Abstract
This document describes Network Management Automation (NMA) of
cellular network services in 5G networks. For NMA, it proposes a
framework empowered with Intent-Based Networking (IBN). The NMA in
this document deals with a closed-loop network control, network
policy translation, and network management audit. To support these
three features in NMA, it specifies an architectural framework with
system components and interfaces. Also, this framework can support
the use cases of NMA in 5G networks such as the data aggregation of
Internet of Things (IoT) devices, network slicing, and the Quality of
Service (QoS) in Vehicle-to-Everything (V2X).
Status of This Memo
This Internet-Draft is submitted in full conformance with the
provisions of BCP 78 and BCP 79.
Internet-Drafts are working documents of the Internet Engineering
Task Force (IETF). Note that other groups may also distribute
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Internet-Drafts are draft documents valid for a maximum of six months
and may be updated, replaced, or obsoleted by other documents at any
time. It is inappropriate to use Internet-Drafts as reference
material or to cite them other than as "work in progress."
This Internet-Draft will expire on 26 October 2023.
Copyright Notice
Copyright (c) 2023 IETF Trust and the persons identified as the
document authors. All rights reserved.
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This document is subject to BCP 78 and the IETF Trust's Legal
Provisions Relating to IETF Documents (https://trustee.ietf.org/
license-info) in effect on the date of publication of this document.
Please review these documents carefully, as they describe your rights
and restrictions with respect to this document. Code Components
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provided without warranty as described in the Revised BSD License.
Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2
2. Terminology . . . . . . . . . . . . . . . . . . . . . . . . . 4
3. Network Management Automation in IBN Framework for 5G
Networks . . . . . . . . . . . . . . . . . . . . . . . . 5
3.1. Components with IBN Framework for Network Management
Automation . . . . . . . . . . . . . . . . . . . . . . . 5
3.2. Interfaces for the IBN Framework . . . . . . . . . . . . 6
4. Network Policy Translation . . . . . . . . . . . . . . . . . 7
5. Network Audit System . . . . . . . . . . . . . . . . . . . . 10
6. A Use Case of IoT Device Data Aggregation . . . . . . . . . . 12
7. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 16
8. Security Considerations . . . . . . . . . . . . . . . . . . . 16
9. References . . . . . . . . . . . . . . . . . . . . . . . . . 17
9.1. Normative References . . . . . . . . . . . . . . . . . . 17
9.2. Informative References . . . . . . . . . . . . . . . . . 17
Appendix A. Acknowledgments . . . . . . . . . . . . . . . . . . 21
Appendix B. Contributors . . . . . . . . . . . . . . . . . . . . 21
Appendix C. Changes from
draft-jeong-nmrg-ibn-network-management-automation-00 . . 21
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 21
1. Introduction
5G networks are evolutionary mobile networks over 4G networks in
terms of high speed, wide bandwidth, high frequency bands, massive
device connectivity, low energy consumption, and intelligence.
Especially, the intelligence will be a key feature to understand the
intents of users and automate network management fully. 5G networks
are designed and implemented on the experience from 4G networks and
new technologies which include Software-Defined Networking (SDN)
[RFC7149] and Network Functions Virtualization (NFV)
[ETSI-NFV][ETSI-NFV-Release-2] along with mmWave for low delivery
delay, high data speed, and large network capacity [TS-23.501].
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The support of network intelligence is one of the main goals of 5G
networks. The network intelligence can provide the 5G networks with
Network Management Automation (NMA) for a self-driving network that
optimizes and adjusts itself by minimizing the interaction with
humans (e.g., network administrators and users).
Intent-Based Networking (IBN) is a feasible approach that can provide
the 5G networks with the NMA services [RFC9315]
[TS-28.312][TR-28.812]. The concept of IBN enables a closed-loop
network control architecture that can adapt to the current status of
a target network by collecting and analyzing monitoring data from
Network Service Functions (NSFs). NSFs can be either Virtual Network
Functions (VNFs) or Physical Network Functions (PNFs) in cloud and
edge computing environments. In the 3rd Generation Partnership
Project (3GPP), Network Data Analytics Function (NWDAF) is defined to
collect and analyze monitoring data from multiple VNFs and PNFs in
cellular networks [TS-23.288][TS-29.520].
For the intelligent NMA services, this document proposes an
architectural framework that combines the IBN and NWDAF to the 5G
networks with Artificial Intelligence (AI) and Machine Learning (ML).
The framework allows an intent from either a network operator or user
to be translated into a high-level policy through a Natural Language
Processing (NLP) technique such as Lumi [USENIX-ATC-Lumi]. The high-
level policy is then translated into a low-level policy through a
Policy Data Model Mapping and a Network Policy Translator (NPT)
[I-D.yang-i2nsf-security-policy-translation]. This low-level policy
is used to remotely configure a network policy into appropriate VNFs
or PNFs in order to enforce the commanded intent in a target network
(e.g., 5G Networks). Also, it also collects and analyzes the
monitoring data from VNFs and PNFs such that the policy can be
verified and optimized to satisfy the requests for the intent.
Therefore, the NMA in this document deals with closed-loop network
control, network policy translation, and network management audit.
To support these three features in NMA, it specifies an architectural
framework with system components and interfaces. In addition, this
framework can support the use cases of NMA in 5G networks such as the
data aggregation of Internet of Things (IoT) devices, network
slicing, and the Quality of Service (QoS) in Vehicle-to-Everything
(V2X). Especially, this document shows a use case of IoT in 5G
networks such as the data collection and analysis of IoT devices.
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2. Terminology
This document uses the terminology described in [RFC8329],
[I-D.ietf-i2nsf-applicability], and
[I-D.jeong-i2nsf-security-management-automation]. In addition, the
following terms are defined below:
* Network Management Automation (NMA): It means that a high-level
network policy from a user (or administrator) is well-enforced in
a target network system. The high-level network policy can be
translated into the corresponding low-level network policy by a
network policy translator and dispatched to appropriate NSFs.
Through the monitoring of the NSFs, the activity and performace of
the NSFs is monitored and analyzed. If needed, the network rules
of the low-level network policy are augmented or new network rules
are generated and configured to appropriate NSFs.
* Network Policy Translation (NPT): It means that a high-level
network policy is translated to a low-level network policy that
can be understood and configured by an NSF for a specific network
service, such as the data aggregation of Internet of Things (IoT)
devices, network slicing, and the Quality of Service (QoS)
provisioning in Vehicle-to-Everything (V2X) communications.
* Feedback-Based Network Management (FNM): It means that a network
service is evolved by updating a network policy (having network
rules) and adding new network rules for detected network problems
by processing and analzing the monitoring data of NSFs.
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+------------+
| IBN User |
+------------+
^
| Consumer-Facing Interface
v
+-------------------+ Registration +-----------------------+
| IBN Controller |<-------------------->| Vendor's Mgmt System |
+-------------------+ Interface +-----------------------+
^ ^
| |
| | Analytics Interface +-----------------------+
| +------------------------>| IBN Analyzer (NWDAF) |
| +-----------------------+
| NSF-Facing Interface ^ ^ ^
| | | |
| | | |
| +------------------------------+ | |
| | +-----------------------+ |
| | | Monitoring Interface |
v v v v
+---------------+ +---------------+ +---------------+
| NSF-1 |--| NSF-2 |........| NSF-n |
|(Policy Control| | (Application | | (IoT Device) |
| Function, PCF)| | Function, AF)| | |
+---------------+ +---------------+ +---------------+
Figure 1: Network Management Automation in IBN Framework for 5G
Networks
3. Network Management Automation in IBN Framework for 5G Networks
This section describes an IBN framework for 5G networks. Note that
this IBN Framework is based on the Framework for Interface to Network
Security Functions (I2NSF)
[RFC8329][I-D.jeong-i2nsf-security-management-automation]. As shown
in Figure 1, an IBN User can use network functions by delivering
high-level network policies, which specify network requirements that
the IBN User wants to enforce, to the IBN Controller via the
Consumer-Facing Interface (CFI).
3.1. Components with IBN Framework for Network Management Automation
The following are the system components for the IBN framework for
network management automation in 5G networks.
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* IBN User: An entity that delivers a high-level network policy to
Security Controller. It is assumed that an intent in a natural
language (e.g., English) can be translated into a high-level
network policy through a Natural Language Processing (called NLP)
technique (e.g., Lumi [USENIX-ATC-Lumi]).
* IBN Controller: An entity that controls and manages other system
components in the IBN framework. It translates a high-level
network policy into the corresponding low-level network policy and
selects appropriate NSFs to execute the network rules of the low-
level network policy.
* Vendor's Management System (VMS): An entity that provides an image
of of a virtualized NSF for a network service to the IBN
framework, and registers the capability and access information of
an NSF with IBN Controller.
* Network Service Function (NSF): An entity that is a Virtual
Network Function (called VNF), Physical Network Function (called
PNF) and Container Network Function (CNF), which is also called
Cloud-native Network Function, for a specific network service such
as the data aggregation of IoT devices, network slicing, and the
QoS provisioning in V2X communications.
* IBN Analyzer: An entity that collects monitoring data from NSFs
and analyzes such data for checking the activity and performance
of the NSFs using machine learning techniques (e.g., Deep Learning
[Deep-Learning]). IBN Analyzer can be a Network Data Analytics
Function (NWDAF) in 5G networks [TS-23.288][TS-29.520]. If there
is a suspicious network problem (e.g., traffic congestion and QoS
degradation) for the target network or NSF, IBN Analyzer delivers
a report of the augmentation or generation of network rules to IBN
Controller.
For IBN-based network services with Feedback-Based Network Management
(FNM), IBN Analyzer is a key IBN component for the IBN framework
[RFC9315] to collect monitoring data from NSFs and analyzing the
monitoring data. The actual implementation of the analysis of
monitoring data is out of the scope of this document.
3.2. Interfaces for the IBN Framework
The following are the interfaces for the IBN framework. Note that
the interfaces can be modeled with YANG [RFC6020] and network
policies are delivered through either RESTCONF [RFC8040] or NETCONF
[RFC6241]. In addition, according to 3GPP specifications, REST API
[REST] can be supported for those interfaces.
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* Consumer-Facing Interface: An interface between IBN User and IBN
Controller for the delivery of a high-level network policy
[I-D.ietf-i2nsf-consumer-facing-interface-dm].
* NSF-Facing Interface: An interface between IBN Controller and an
NSF for the delivery of a low-level network policy
[I-D.ietf-i2nsf-nsf-facing-interface-dm].
* Registration Interface: An interface between a VMS and IBN
Controller for the registration of an NSF's capability and access
information with the IBN Controller or the query of an NSF for a
required low-level network policy
[I-D.ietf-i2nsf-registration-interface-dm].
* Monitoring Interface: An interface between an NSF and IBN Analyzer
for collecting monitoring data from an NSF to check the activity
and performance of an NSF for a possible network problem
[I-D.ietf-i2nsf-nsf-monitoring-data-model].
* Analytics Interface: An interface between IBN Analyzer and IBN
Controller for the delivery of an analytics report of the
augmentation or generation of network rules to IBN Controller,
which lets IBN Controller apply the report for network rules to
its network policy management.
For IBN-based network services with FSM, Analytics Interface is a key
interface in the IBN framework to deliver an analytics report of the
augmentation or generation of network rules to IBN Controller through
the analysis of the monitoring data from NSFs.
4. Network Policy Translation
To facilitate Network Policy Translation (NPT), IBN Controller needs
to have a network policy translator that performs the translation of
a high-level network policy into the corresponding low-level network
policy. For the automatic NPT services, the IBN framework needs to
bridge a high-level YANG data model and a low-level YANG data model
in an automatic manner [I-D.yang-i2nsf-security-policy-translation].
Note that a high-level YANG data model is for the IBN Consumer-Facing
Interface, and a low-level YANG data model is for the IBN NSF-Facing
Interface.
Figure 2 shows automatic mapping of high-level and low-level data
models for network policies. Automatic Data Model Mapper takes a
high-level YANG data module for the Consumer-Facing Inteface and a
low-level YANG data module for the NSF-Facing Interface. It then
constructs a mapping table associating the data attributes (or
variables) of the high-level YANG data module with the corresponding
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data attributes (or variables) of the low-level YANG data module.
Also, it generates a set of production rules of the grammar for the
construction of an XML file of low-level network policy rules.
Figure 3 shows the procedure of high-to-low network policy
translation. A network policy translator is a component of IBN
Controller. The translator consists of three components such as
Policy Data Model Mapper, Policy Data Extractor, Policy Data
Converter, and Policy Generator.
High-level YANG Data Module Low-level YANG Data Model
| |
V V
+---------+------------------------------+---------+
| Policy Data Model Mapper |
+------------------------+-------------------------+
|
Mapping Model (Data Model Mapping Table)
|
V
+--------------------------------------------------+
| NSF Database |
+--------------------------------------------------+
Figure 2: Automatic Mapping of High-level and Low-level Data Models
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+-------------------------------------------------+
| |
| IBN User |
| |
+------------------------+------------------------+
| Consumer-Facing Interface
|
High-level Network Policy
|
IBN Controller V
+--------------------------+-----------------------------------------------+
| Network Policy | |
| Translator V |
| +-----------------------+--------------------------------------------+ |
| | | | |
| | V | |
| | +---------------+-------+ +--------------------------+ | |
| | | Policy Data Extractor | | Policy Data Model Mapper | | |
| | +---------------+-------+ +--------+-----------------+ | |
| | | | Mapping | |
| | V V Model | |
| | +---------------+-------+ +--------------------+ | |
| | | Policy Data Converter |<---->| NSF Database | | |
| | +---------------+-------+ +--------------------+ | |
| | | | |
| | V | |
| | +---------------+-------+ | |
| | | Policy Generator | | |
| | +---------------+-------+ | |
| | | | |
| | V | |
| +-----------------------+--------------------------------------------+ |
| | |
| V |
+--------------------------+-----------------------------------------------+
| NSF-Facing Interface
|
Low-level Network Policy
|
V
+------------------------+-------------------------+
| |
| NSF(s) |
| |
+--------------------------------------------------+
Figure 3: High-to-Low Network Policy Translation
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Policy Data Model Mapper maps the attributes and their values of a
high-level network policy to the corresponding attributes and their
values of a low-level network policy. Note that the values of a
high-level network policy may involve a human language and must be
converted to an appropriate value for a low-level network policy
(e.g., employees -> 192.0.1.0/24).
Policy Data Extractor extracts the values of the attributes related
to a network policy from a high-level network policy that was
delivered by an IBN User to an IBN Controller through the Consumer-
Facing Interface [I-D.ietf-i2nsf-consumer-facing-interface-dm].
Policy Data Converter converts the values of the high-level policy's
attributes into the values of the corresponding low-level policy's
attributes to generate the low-level network policy
[I-D.ietf-i2nsf-nsf-facing-interface-dm].
Policy Generator generates the corresponding low-level network policy
that is delivered by the IBN Controller to an appropriate NSF through
NSF-Facing Interface [I-D.ietf-i2nsf-nsf-facing-interface-dm].
5. Network Audit System
The IBN framework is weak to both an insider attack and a supply
chain attack since it trusts in NSFs provided by VMS and assumes that
NSFs work for their network services appropriately
[I-D.ietf-i2nsf-applicability].
To detect the malicious activity of either an insider attack by a
malicious VMS or a supply chain attack by a compromised VMS, a
network audit system is required by the IBN framework. This network
audit system can facilitate the non-repudiation of configuration
commands and monitoring data generated in the IBN framework.
A network audit system has the following four main objectives:
* To check the existence of a network policy, a management system,
and its procedures;
* To identify and understand the existing vulnerabilities and risks
of either an insider attack or a supply chain attack;
* To review existing network controls on operational and
administrative issues;
* To provide recommendations and corrective actions to IBN
Controller for further network and security improvement.
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+-----------------------------+ +----------------+
| IBN User | | Vendor's Mgmt |
| +------------+ | System |
+--------------+--------------+ | +--------+-------+
| Consumer-Facing Interface | |
| | Remote |
High-level Security Policy | Attestation |
| | Interface |
| | |
V | V
+--------------+--------------+ | +---------+--------+
| | V | Network |
| IBN Controller +------------+---->| Audit |
| | ^ | System |
+--------------+--------------+ | +---------+--------+
| NSF-Facing Interface | ^
| | Remote |
Low-level Security Policy | Attestation |
| | Interface |
V | |
+--------------+--------------+ | +--------+-------+
| NSF(s) +------------+ | IBN Analyzer |
| +------------------>| |
+-----------------------------+ Monitoring +----------------+
Interface
Figure 4: Activity Auditing with Network Audit System
Figure 4 shows activity auditing with a network audit system in the
IBN framework. All the components in the IBN framwork report its
activities (such as configuration commands and monitoring data) to
Network Audit System as transactions through Remote Attestation
Interface [I-D.yang-i2nsf-remote-attestation-interface-dm]. The
network audit system can analyze the reported activities from the IBN
components to detect malicious activities such as an insider attack
and a supply chain attack. Note that such a network audit system can
be implemented by remote attestation [I-D.ietf-rats-architecture][I-D
.yang-i2nsf-remote-attestation-interface-dm] or Blockchain [Bitcoin].
The details of the implementation of the network audit system are out
of the scope of this document.
In order to determine a minimum set of controls required to reduce
the risks from either an insider attack or a supply chain attack, the
network audit system should analyze the activities of all the
components in the IBN framework periodically, evaluate possible
risks, and take an action to such risks since vulnerabilities and
threats may change in different environments over time.
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6. A Use Case of IoT Device Data Aggregation
This section describes a use case where a policy of IoT device data
aggregation is set up in the IBN framework for 5G networks.
Figure 5 shows the procedure of the enforcement for an IoT device
data aggregation policy in the IBN Framework as follows:
1. IBN User sends a High-level Policy Request to IBN Controller.
2. IBN Controller translates the request with its Network Policy
Translator (called NPT). The NPT identifies NSFs (i.e., IoT
Devices) for the request after the steps of Policy Data
Extraction and Policy Data Conversion.
3. If the NSFs are available for the requested network policy, go
to the step of Policy Generation in NPT. If the NSFs are
unavailable for the requested network policy, go to the next
step.
4. IBN Controller sends an NSF Query Request to Vendor's Management
System (called VMS) to find an appropriate NSF for the request
network policy.
5. If there is such an NSF registered with VMS, VMS sends an NSF
Initializtion Request to Cloud (or Edge Server) to initialize
the NSF.
6. Cloud (or Edge Server) forwards the NSF Initializtion Request to
the appropriate NSF to let it initialize itself.
7. The NSF performs an initialization to perform a task for a
network policy in 5G networks.
8. The NSF sends an NSF Initialization Response to Cloud (or Edge
Server) to tell Cloud (or Edge Server) its readiness to perform
a task.
9. Cloud (or Edge Server) forwards the NSF Initialization Response
to VMS to tell an NSF's readiness to perform a task.
10. VMS sends an NSF Query Response to IBN Controller to tell an
NSF's readiness to perform a task along with the network access
information for the NSF.
11. IBN Controller performs the step of Policy Generation in its NPT
along with the network access information of an appropriate
NSF(s).
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12. IBN Controller sends a Low-level Policy Request to the
appropriate NSF.
13. The NSF performs the configration in the given Low-level Policy
Request to perform the requested task (e.g., sensing and
reporting).
14. The NSF sends a Low-level Policy Response to IBN Controller to
tell its readiness to perform the requested task.
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IBN IBN Vendor's Cloud NSF1
User Controller Mgmt System (or Edge Server) (IoT Device)
| | | | |
|-High-level--->| | | |
| Policy Request| | | |
| | | | |
| Translation: | | |
| Data Extraction & | | |
| Data Conversion | | |
| | | | |
|*** Case 1: NSFs available: Go to Policy Generation *** |
| | | | |
|*** Case 2: NSFs unavailable (START) *** | |
| | | | |
| |-NSF Query------>| | |
| | Request |-NSF Initiation->| |
| | | Request | |
| | | |-NSF Initiation->|
| | | | Request |
| | | | |
| | | | NSF
| | | | Initialization
| | | | |
| | | |<-NSF Initiation-|
| | |<-NSF Initiation-| Response |
| |<-NSF Query------| Response | |
| | Response | | |
| | | | |
|*** Case 2: NSFs unavailable (END) *** | |
| | | | |
| Translation: | | |
| Policy Generation | | |
| | | | |
| |--Low-level Policy Request-------------------------->|
| | | | |
| | | | NSF
| | | | Configuration
| | | | |
| |<-Low-level Policy Response--------------------------|
| | | | |
Figure 5: Procedure of an IoT Device Data Aggregation Policy
Enforcement in the IBN Framework
Figure 6 shows the procedure of the reporting for IoT device data
aggregation in the IBN Framework as follows:
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1. NSF1 (as an IoT Device) sends its Sensing Data to IBN Analyzer
(as an NWDAF).
2. NSF2 (as an IoT Device) sends its Sensing Data to IBN Analyzer
(as an NWDAF).
3. IBN Analyzer performs Sensing Data Aggregation and analyzes the
aggregated sensing data through Machine Learning (ML) techniques.
It then generates a Sensing Report for IBN Controller.
4. IBN Analyzer sends a Sensing Report to IBN Controller.
5. IBN Controller analyzes the Sensing Report for a further action.
If a further action is needed, it updates the existing network
policy or generates a new network policy.
6. IBN Controller sends the report for the further action to IBN
User optionally if the reporting is needed.
7. For the further action, IBN Controller sends an Updated NSF
Policy Request or a New NSF Policy Request to the appropriate
NSF(s).
8. The appropriate NSF(s) reconfigures the Updated NSF Policy or
configures the new NSF Policy in its own system.
9. The appropriate NSF(s) sends an Updated NSF Policy Response or a
NEW NSF Policy Response to IBN Controller.
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IBN IBN IBN NSF1 NSF2
User Controller Analyzer (IoT Device) (IoT Device)
| | | | |
| | |<----Sensing-----| |
| | | Data | |
| | | | |
| | |<----Sending-----------------------|
| | | Data | |
| | | | |
| | Sensing | |
| | Data | |
| | Aggregation | |
| | | | |
| |<---Sensing------| | |
| | Report | | |
| | | | |
| Policy | | |
| Update | | |
| (or Generation) | | |
| | | | |
|<---Report-----| | | |
| |--Updated/New Low-level Policy Request-------------->|
| | | | |
| | | | NSF
| | | | (Re)Configuration
| | | | |
| |<-Updated/New Low-level Policy Response--------------|
| | | | |
Figure 6: Procedure of IoT Device Data Aggregation Reporting in
the IBN Framework
7. IANA Considerations
This document does not require any IANA actions.
8. Security Considerations
The same security considerations for the IBN framework [RFC8329] are
applicable to this document.
The development and introduction of IBN Analyzer and Network Audit
System in the IBN Framework may create new security concerns that
have to be anticipated at the design and specification time. The
usage of machine learning to analyze monitoring data of malicious
NSFs may add a risk to its model to be attacked (e.g., adversarial
attack) and can result in a bad security policy that is deployed into
the IBN system.
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9. References
9.1. Normative References
[RFC6020] Bjorklund, M., Ed., "YANG - A Data Modeling Language for
the Network Configuration Protocol (NETCONF)", RFC 6020,
DOI 10.17487/RFC6020, October 2010,
<https://www.rfc-editor.org/info/rfc6020>.
[RFC6241] Enns, R., Ed., Bjorklund, M., Ed., Schoenwaelder, J., Ed.,
and A. Bierman, Ed., "Network Configuration Protocol
(NETCONF)", RFC 6241, DOI 10.17487/RFC6241, June 2011,
<https://www.rfc-editor.org/info/rfc6241>.
[RFC8040] Bierman, A., Bjorklund, M., and K. Watsen, "RESTCONF
Protocol", RFC 8040, DOI 10.17487/RFC8040, January 2017,
<https://www.rfc-editor.org/info/rfc8040>.
[RFC8329] Lopez, D., Lopez, E., Dunbar, L., Strassner, J., and R.
Kumar, "Framework for Interface to Network Security
Functions", RFC 8329, DOI 10.17487/RFC8329, February 2018,
<https://www.rfc-editor.org/info/rfc8329>.
[RFC9315] Clemm, A., Ciavaglia, L., Granville, L. Z., and J.
Tantsura, "Intent-Based Networking - Concepts and
Definitions", RFC 9315, DOI 10.17487/RFC9315, October
2022, <https://www.rfc-editor.org/info/rfc9315>.
9.2. Informative References
[I-D.ietf-i2nsf-consumer-facing-interface-dm]
Jeong, J. P., Chung, C., Ahn, T., Kumar, R., and S. Hares,
"I2NSF Consumer-Facing Interface YANG Data Model", Work in
Progress, Internet-Draft, draft-ietf-i2nsf-consumer-
facing-interface-dm-30, 17 April 2023,
<https://datatracker.ietf.org/doc/html/draft-ietf-i2nsf-
consumer-facing-interface-dm-30>.
[I-D.ietf-i2nsf-nsf-facing-interface-dm]
Kim, J. T., Jeong, J. P., Jung-Soo, J., Hares, S., and Q.
Lin, "I2NSF Network Security Function-Facing Interface
YANG Data Model", Work in Progress, Internet-Draft, draft-
ietf-i2nsf-nsf-facing-interface-dm-29, 1 June 2022,
<https://datatracker.ietf.org/doc/html/draft-ietf-i2nsf-
nsf-facing-interface-dm-29>.
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[I-D.ietf-i2nsf-registration-interface-dm]
Hyun, S., Jeong, J. P., Roh, T., Wi, S., and J. Jung-Soo,
"I2NSF Registration Interface YANG Data Model for NSF
Capability Registration", Work in Progress, Internet-
Draft, draft-ietf-i2nsf-registration-interface-dm-25, 17
April 2023, <https://datatracker.ietf.org/doc/html/draft-
ietf-i2nsf-registration-interface-dm-25>.
[I-D.ietf-i2nsf-nsf-monitoring-data-model]
Jeong, J. P., Lingga, P., Hares, S., Xia, L., and H.
Birkholz, "I2NSF NSF Monitoring Interface YANG Data
Model", Work in Progress, Internet-Draft, draft-ietf-
i2nsf-nsf-monitoring-data-model-20, 1 June 2022,
<https://datatracker.ietf.org/doc/html/draft-ietf-i2nsf-
nsf-monitoring-data-model-20>.
[I-D.ietf-i2nsf-applicability]
Jeong, J. P., Hyun, S., Ahn, T., Hares, S., and D. Lopez,
"Applicability of Interfaces to Network Security Functions
to Network-Based Security Services", Work in Progress,
Internet-Draft, draft-ietf-i2nsf-applicability-18, 16
September 2019, <https://datatracker.ietf.org/doc/html/
draft-ietf-i2nsf-applicability-18>.
[I-D.jeong-i2nsf-security-management-automation]
Jeong, J. P., Lingga, P., Jung-Soo, J., Lopez, D., and S.
Hares, "Security Management Automation of Cloud-Based
Security Services in I2NSF Framework", Work in Progress,
Internet-Draft, draft-jeong-i2nsf-security-management-
automation-05, 30 January 2023,
<https://datatracker.ietf.org/doc/html/draft-jeong-i2nsf-
security-management-automation-05>.
[I-D.yang-i2nsf-security-policy-translation]
Jeong, J. P., Lingga, P., Yang, J., and J. Kim,
"Guidelines for Security Policy Translation in Interface
to Network Security Functions", Work in Progress,
Internet-Draft, draft-yang-i2nsf-security-policy-
translation-14, 28 March 2023,
<https://datatracker.ietf.org/doc/html/draft-yang-i2nsf-
security-policy-translation-14>.
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[I-D.ietf-rats-architecture]
Birkholz, H., Thaler, D., Richardson, M., Smith, N., and
W. Pan, "Remote ATtestation procedureS (RATS)
Architecture", Work in Progress, Internet-Draft, draft-
ietf-rats-architecture-22, 28 September 2022,
<https://datatracker.ietf.org/doc/html/draft-ietf-rats-
architecture-22>.
[I-D.yang-i2nsf-remote-attestation-interface-dm]
Yang, P., chenmeiling, Su, L., Lopez, D., Jeong, J. P.,
and L. Dunbar, "I2NSF Remote Attestation Interface YANG
Data Model", Work in Progress, Internet-Draft, draft-yang-
i2nsf-remote-attestation-interface-dm-01, 5 June 2022,
<https://datatracker.ietf.org/doc/html/draft-yang-i2nsf-
remote-attestation-interface-dm-01>.
[TS-23.501]
"System Architecture for the 5G System (5GS)", Available:
https://portal.3gpp.org/desktopmodules/Specifications/
SpecificationDetails.aspx?specificationId=3144, September
2022.
[TS-28.312]
"Intent Driven Management Services for Mobile Networks",
Available:
https://portal.3gpp.org/desktopmodules/Specifications/
SpecificationDetails.aspx?specificationId=3554, September
2022.
[TR-28.812]
"Study on Scenarios for Intent Driven Management Services
for Mobile Networks", Available:
https://portal.3gpp.org/desktopmodules/Specifications/
SpecificationDetails.aspx?specificationId=3553, December
2020.
[TS-23.288]
"Architecture Enhancements for 5G System (5GS) to Support
Network Data Analytics Services", Available:
https://portal.3gpp.org/desktopmodules/Specifications/
SpecificationDetails.aspx?specificationId=3579, September
2022.
[TS-29.520]
"Network Data Analytics Services", Available:
https://portal.3gpp.org/desktopmodules/Specifications/
SpecificationDetails.aspx?specificationId=3355, September
2022.
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[RFC7149] Boucadair, M. and C. Jacquenet, "Software-Defined
Networking: A Perspective from within a Service Provider
Environment", RFC 7149, March 2014,
<https://www.rfc-editor.org/rfc/rfc7149>.
[ETSI-NFV] "Network Functions Virtualisation (NFV); Architectural
Framework", Available:
https://www.etsi.org/deliver/etsi_gs/
nfv/001_099/002/01.02.01_60/gs_nfv002v010201p.pdf,
December 2014.
[ETSI-NFV-Release-2]
"Network Functions Virtualisation (NFV) Release 2;
Management and Orchestration; Architectural Framework
Specification", Available:
https://www.etsi.org/deliver/etsi_gs/
nfv/001_099/006/02.01.01_60/gs_nfv006v020101p.pdf, January
2021.
[Bitcoin] Nakamoto, S., "Bitcoin: A Peer-to-Peer Electronic Cash
System", Available: https://bitcoin.org/bitcoin.pdf, May
2009.
[USENIX-ATC-Lumi]
Jacobs, A., Pfitscher, R., Ribeiro, R., Ferreira, R.,
Granville, L., Willinger, W., and S. Rao, "Hey, Lumi!
Using Natural Language for Intent-Based Network
Management", USENIX Annual Technical Conference,
Available:
https://www.usenix.org/conference/atc21/presentation/
jacobs, July 2021.
[REST] Fielding, R. and R. Taylor, "Principled Design of the
Modern Web Architecture", ACM Transactions on Internet
Technology, Vol. 2, Issue 2,,
Available: https://dl.acm.org/doi/10.1145/514183.514185,
May 2002.
[Deep-Learning]
Goodfellow, I., Bengio, Y., and A. Courville, "Deep
Learning", Publisher: The MIT Press,
URL: https://www.deeplearningbook.org/, November 2016.
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Appendix A. Acknowledgments
This work was supported by Institute of Information & Communications
Technology Planning & Evaluation (IITP) grant funded by the Korea
Ministry of Science and ICT (MSIT)(No. 2022-0-01015, Development of
Candidate Element Technology for Intelligent 6G Mobile Core Network).
This work was supported in part by Institute of Information &
Communications Technology Planning & Evaluation (IITP) grant funded
by the Korea Ministry of Science and ICT (MSIT) (No. 2022-0-01199,
Regional strategic industry convergence security core talent training
business).
Appendix B. Contributors
This document is made by the group effort of NMRG. Many people
actively contributed to this document, such as Linda Dunbar, Yoav
Nir, Susan Hares, and Qin Wu. The authors sincerely appreciate their
contributions.
The following are co-authors of this document:
Patrick Lingga - Department of Electronic, Electrical and Computer
Engineering, Sungkyunkwan University, 2066 Seobu-Ro Jangan-Gu, Suwon,
Gyeonggi-do 16419, Republic of Korea. EMail: patricklink@skku.edu
Jung-Soo Park - Electronics and Telecommunications Research
Institute, 218 Gajeong-Ro, Yuseong-Gu, Daejeon, 34129, Republic of
Korea. EMail: pjs@etri.re.kr
Yunchul Choi - Electronics and Telecommunications Research Institute,
218 Gajeong-Ro, Yuseong-Gu, Daejeon, 34129, Republic of Korea.
EMail: cyc79@etri.re.kr
Appendix C. Changes from draft-jeong-nmrg-ibn-network-management-
automation-00
The following changes are made from draft-jeong-nmrg-ibn-network-
management-automation-00:
* There is an update of the author list.
* There are updates in the References.
Authors' Addresses
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Jaehoon Paul Jeong (editor)
Department of Computer Science and Engineering
Sungkyunkwan University
2066 Seobu-Ro, Jangan-Gu
Suwon
Gyeonggi-Do
16419
Republic of Korea
Phone: +82 31 299 4957
Email: pauljeong@skku.edu
URI: http://iotlab.skku.edu/people-jaehoon-jeong.php
Jeonghyeon Kim
Department of Computer Science and Engineering
Sungkyunkwan University
2066 Seobu-Ro, Jangan-Gu
Suwon
Gyeonggi-Do
16419
Republic of Korea
Phone: +82 31 299 4957
Email: jeonghyeon12@skku.edu
Yongjun Noh
Department of Computer Science and Engineering
Sungkyunkwan University
2066 Seobu-Ro, Jangan-Gu
Suwon
Gyeonggi-Do
16419
Republic of Korea
Phone: +82 31 299 4957
Email: n0y0j@g.skku.edu
Younghan Kim
School of Electronic Engineering
Soongsil University
369, Sangdo-ro, Dongjak-gu
Seoul
06978
Republic of Korea
Phone: +82 10 2691 0904
Email: younghak@ssu.ac.kr
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