Internet-Draft | I2NSF Security Management Automation | January 2023 |
Jeong, et al. | Expires 3 August 2023 | [Page] |
This document describes Security Management Automation (SMA) of cloud-based security services in the framework of Interface to Network Security Functions (I2NSF). The security management automation in this document deals with closed-loop security control, security policy translation, and security audit. To support these three features in SMA, this document specifies an augmented architecture of the I2NSF framework with new system components and new interfaces.¶
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Interface to Network Security Functions (I2NSF) defines a framework and interfaces for interacting with Network Security Functions (NSFs) [RFC8192][RFC8329]. Note that an NSF is defined as software that provides a set of security-related services, such as (i) detecting unwanted activity, (ii) blocking or mitigating the effect of such unwanted activity in order to fulfill service requirements, and (iii) supporting communication stream integrity and confidentiality [RFC8329]. The NSF can be implemented as a Virtual Network Function (VNF) in a Network Functions Virtualization (NFV) environment [ETSI-NFV][I-D.ietf-i2nsf-applicability].¶
This document describes Security Management Automation (SMA) of cloud-based security services in the I2NSF framework. The security management automation includes closed-loop security control, security policy translation, and security audit. This document specifies an augmented architecture of the I2NSF framework for the SMA services with new system components and new interfaces.¶
For reliable management for networked security services, this document proposes a network management and verification facility using a secuirty audit system (e.g., remote attestation and blockchain [Bitcoin]). This security audit system can facilitate the non-repudiation of configuration commands and monitoring data generated in the I2NSF framework.¶
Therefore, with the security service automation, this document facilitates the foundation of Intent-Based Networking (IBN) for autonomous security services [RFC9315].¶
This document uses the terminology described in [RFC8329] and [I-D.ietf-i2nsf-applicability]. In addition, the following terms are defined below:¶
This section summarizes the I2NSF framework as defined in [RFC8329]. As shown in Figure 1, an I2NSF User can use security functions by delivering high-level security policies, which specify security requirements that the I2NSF user wants to enforce, to the Security Controller via the Consumer-Facing Interface (CFI) [I-D.ietf-i2nsf-consumer-facing-interface-dm].¶
The following are the system components for the SMA-based I2NSF framework.¶
For SMA-based security services with Feedback-Based Security Management (FSM), I2NSF Analyzer is required as a new I2NSF component for the legacy I2NSF framework [RFC8329] 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.¶
The following are the interfaces for the SMA-based I2NSF framework. Note that the interfaces are modeled with YANG [RFC6020] and security policies are delivered through either RESTCONF [RFC8040] or NETCONF [RFC6241].¶
For SMA-based security services with FSM, Analytics Interface is required as a new I2NSF interface for the legacy I2NSF framework [RFC8329] to deliver an analytics report of the augmentation or generation of security rules to Security Controller through the analysis of the monitoring data from NSFs.¶
To facilitate Security Policy Translation (SPT), Security Controller needs to have a security policy translator that performs the translation of a high-level security policy into the corresponding low-level security policy. For the automatic SPT services, the I2NSF framework needs to bridge a high-level YANG data model and a low-level YANG data model in an automatic manner [I-D.ietf-i2nsf-applicability][I-D.yang-i2nsf-security-policy-translation]. Note that a high-level YANG data model is for the I2NSF Consumer-Facing Interface [I-D.ietf-i2nsf-consumer-facing-interface-dm], and a low-level YANG data model is for the I2NSF NSF-Facing Interface [I-D.ietf-i2nsf-nsf-facing-interface-dm].¶
Figure 2 shows automatic mapping of high-level and low-level data models. 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 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 security policy rules.¶
Figure 3 shows high-to-low security policy translation. A security policy translator is a component of Security Controller. The translator consists of three components such as Data Model Mapper, Data Extractor, Data Converter, and Policy Generator.¶
Data Model Mapper maps the attributes and their values of a high-level security policy to the corresponding attributes and their values of a low-level security policy. Note that the values of a high-level security policy may involve a human language and must be converted to an appropriate value for a low-level security policy (e.g., employees -> 192.0.1.0/24).¶
Data Extractor extracts the values of the attributes related to a security policy from a high-level security policy that was delivered by an I2NSF User to a Security Controller through the Consumer-Facing Interface [I-D.ietf-i2nsf-consumer-facing-interface-dm].¶
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 security policy [I-D.ietf-i2nsf-nsf-facing-interface-dm].¶
Policy Generator generates the corresponding low-level security policy that is delivered by the Security Controller to an appropriate NSF through NSF-Facing Interface [I-D.ietf-i2nsf-nsf-facing-interface-dm].¶
The I2NSF framework is weak to both an insider attack and a supply chain attack since it trusts in NSFs provided by Developer's Management System (DMS) and assumes that NSFs work for their security services appropriately [I-D.ietf-i2nsf-applicability].¶
To detect the malicious activity of either an insider attack by a malicious DMS or a supply chain attack by a compromised DMS, a security audit system is required by the I2NSF framework. This security audit system can facilitate the non-repudiation of configuration commands and monitoring data generated in the I2NSF framework.¶
A security audit system has the following four main objectives:¶
Figure 4 shows activity auditing with a security audit system in the I2NSF framework. All the components in the I2NSF framwork report its activities (such as configuration commands and monitoring data) to Security Audit System as transactions through Remote Attestation Interface [I-D.yang-i2nsf-remote-attestation-interface-dm]. The security audit system can analyze the reported activities from the I2NSF components to detect malicious activities such as an insider attack and a supply chain attack. Note that such a security audit system can be implemented by remote attestation [RFC9334][I-D.yang-i2nsf-remote-attestation-interface-dm] or Blockchain [Bitcoin]. The details of the implementation of the security 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 security audit system should analyze the activities of all the components in the I2NSF framework periodically, evaluate possible risks, and take an action to such risks since vulnerabilities and threats may change in different environments over time.¶
This document does not require any IANA actions.¶
The same security considerations for the I2NSF framework [RFC8329] are applicable to this document.¶
The development and introduction of I2NSF Analyzer and Security Audit System in the I2NSF 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 I2NSF system.¶
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) (2020-0-00395-003, Standard Development of Blockchain based Network Management Automation Technology). This work was supported by the IITP grant funded by the Korea MSIT (R-20160222-002755, Cloud based Security Intelligence Technology Development for the Customized Security Service Provisioning).¶
This document is made by the group effort of I2NSF working group. Many people actively contributed to this document, such as Linda Dunbar, Yoav Nir, and Qin Wu. The authors sincerely appreciate their contributions.¶
The following are co-authors of this document:¶
Jeonghyeon Kim - Department of Computer Science and Engineering, Sungkyunkwan University, 2066 Seobu-ro Jangan-gu, Suwon, Gyeonggi-do 16419, Republic of Korea. EMail: jeonghyeon12@skku.edu¶
Yunchul Choi - Electronics and Telecommunications Research Institute, 218 Gajeong-Ro, Yuseong-Gu, Daejeon, 34129, Republic of Korea. EMail: cyc79@etri.re.kr¶
Younghan Kim - School of Electronic Engineering, Soongsil University, 369, Sangdo-ro, Dongjak-gu, Seoul 06978, Republic of Korea. EMail: younghak@ssu.ac.kr¶
The following changes are made from draft-jeong-i2nsf-security-management-automation-04:¶