Internet-Draft | I2NSF Security Management Automation | February 2024 |
Jeong, et al. | Expires 10 August 2024 | [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:¶
Security Management Automation (SMA): It means that a high-level security policy from a user (or administrator) is well-enforced in a target I2NSF system. The high-level security policy can be translated into the corresponding low-level security policy by a security 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 security rules of the low-level security policy are augmented or new security rules are generated and configured to appropriate NSFs.¶
Security Policy Translation (SPT): It means that a high-level security policy is translated to a low-level security policy that can be understood and configured by an NSF for a specific security service, such as firewall, web filter, deep packet inspection, DDoS-attack mitigation, and anti-virus.¶
Feedback-Based Security Management (FSM): It means that a security service is evolved by updating a security policy (having security rules) and adding new security rules for detected security attacks by processing and analzing the monitoring data of NSFs.¶
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.¶
I2NSF User: An entity that delivers a high-level security policy to Security Controller.¶
Security Controller: An entity that controls and manages other system components in the I2NSF framework. It translates a high-level security policy into the corresponding low-level security policy and selects appropriate NSFs to execute the security rules of the low-level security policy.¶
Developer's Management System (DMS): An entity that provides an image of of a virtualized NSF for a security service to the I2NSF framework, and registers the capability and access information of an NSF with Security Controller.¶
Network Security Function (NSF): An entity that is a Virtual Network Function (VNF) or Container Network Function (CNF), which is called Cloud-native Network Function, for a specific network security service such as firewall, web filter, deep packet inspection, DDoS-attack mitigation, and anti-virus.¶
I2NSF 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]). If there is a suspicious attack activity for the target network or NSF, I2NSF Analyzer delivers a report of the augmentation or generation of security rules to Security Controller.¶
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].¶
Consumer-Facing Interface: An interface between I2NSF User and Security Controller for the delivery of a high-level security policy [I-D.ietf-i2nsf-consumer-facing-interface-dm].¶
NSF-Facing Interface: An interface between Security Controller and an NSF for the delivery of a low-level security policy [I-D.ietf-i2nsf-nsf-facing-interface-dm].¶
Registration Interface: An interface between a DMS and Security Controller for the registration of an NSF's capability and access information with the Security Controller or the query of an NSF for a required low-level security policy [I-D.ietf-i2nsf-registration-interface-dm].¶
Monitoring Interface: An interface between an NSF and I2NSF Analyzer for collecting monitoring data from an NSF to check the activity and performance of an NSF for a possible malicious traffic [I-D.ietf-i2nsf-nsf-monitoring-data-model].¶
Analytics Interface: An interface between I2NSF Analyzer and Security Controller for the delivery of an analytics report of the augmentation or generation of security rules to Security Controller [I-D.lingga-i2nsf-analytics-interface-dm]. This interface lets Security Controller get the report for security rules to its security policy management.¶
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:¶
To check the existence of a security 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 security controls on operational and administrative issues;¶
To provide recommendations and corrective actions to Security Controller for further security improvement.¶
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 document benefited from discussions in the I2NSF Working Group, especially from Linda Dunbar and Yoav Nir. This document took advantage of the review and comments from the following experts: Qin Wu and Adrian Farrel. The authors sincerely appreciate their sincere efforts and kind help.¶
This work was supported 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 in part by Institute of Information & Communications Technology Planning & Evaluation (IITP) grant funded by the Korea Ministry of Science and ICT (MSIT)(No. 2022-0-01015, Development of Candidate Element Technology for Intelligent 6G Mobile Core Network).¶
The following are coauthors of this document:¶
The following changes are made from draft-jeong-i2nsf-security-management-automation-06:¶
This version is for only maintenance.¶