Department of Computer Science and Engineering

Sungkyunkwan University 2066 Seobu-Ro, Jangan-Gu Suwon Gyeonggi-Do 16419 Republic of Korea +82 31 299 4957 +82 31 290 7996 pauljeong@skku.edu http://iotlab.skku.edu/people-jaehoon-jeong.php

Department of Electronic, Electrical and Computer Engineering

Sungkyunkwan University 2066 Seobu-Ro, Jangan-Gu Suwon Gyeonggi-Do 16419 Republic of Korea +82 31 299 4957 patricklink@skku.edu

Electronics and Telecommunications Research Institute

218 Gajeong-Ro, Yuseong-Gu Daejeon 305-700 Republic of Korea +82 42 860 6514 pjs@etri.re.kr

Security I2NSF Working Group Internet-Draft This document describes an extension of the framework of Interface to Network Security Functions (I2NSF) for Security Management Automation (SMA) in cloud-based security services. The security management automation in this document deals with a security polity translation and a feedback-based security service enforcement. To support these two features in SMA, this document specifies an augmented architecture of the I2NSF framework with a new system component and a new interface.

Interface to Network Security Functions (I2NSF) defines a framework and interfaces for interacting with Network Security Functions (NSFs) . 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 . The NSF can be implemented as a Virtual Network Function (VNF) in a Network Functions Virtualization (NFV) environment . This document describes an extension of the framework of Interface to Network Security Functions (I2NSF) for Security Management Automation (SMA) in cloud-based security services. The security management automation includes a security polity translation and a feedback-based security service enforcement. This document specifies an augmented architecture of the I2NSF framework for the SMA services with a new system component and a new interface. For reliable management for networked security services, this document proposes a network management and verification facility using a decentralized audit system (e.g., blockchain ). This 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 intelligent security services .

This document uses the terminology described in and . 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.

|Developer's Mgmt System| +-------------------+ Interface +-----------------------+ ^ ^ | | | | Application Interface +-----------------------+ | +------------------------>| I2NSF Analyzer | | +-----------------------+ | NSF-Facing Interface ^ ^ ^ | | | | | | | | | +------------------------------+ | | | | +-----------------------+ | | | | Monitoring Interface | v v v v +----------------+ +---------------+ +-----------------------+ | NSF-1 |-| NSF-2 |...| NSF-n | | (Firewall) | | (Web Filter) | |(DDoS-Attack Mitigator)| +----------------+ +---------------+ +-----------------------+ ]]>

This section summarizes the I2NSF framework as defined in . As shown in , 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) .

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) 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 ). 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 as a new I2NSF component is required for the legacy I2NSF framework to collect monitoring data of NSFs and analyzing them. The actual implementation of monitoring data analysis 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 and security policies are delivered through either RESTCONF or NETCONF . Consumer-Facing Interface: An interface between I2NSF User and Security Controller for the delivery of a high-level security policy . NSF-Facing Interface: An interface between Security Controller and an NSF for the delivery of a low-level security policy . 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 . 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 . Application Interface: An interface between I2NSF Analyzer and Security Controller for the delivery of a report of the augmentation or generation of security rules to Security Controller, which lets Security Controller apply the report for security rules to its security policy management. For SMA-based security services with FSM, Application Interface as a new I2NSF interface is required for the legacy I2NSF framework to deliver a report of the augmentation or generation of security rules to Security Controller on the basis of the analyzed monitoring data of 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 . Note that a high-level YANG data model is for the I2NSF Consumer-Facing Interface , and a low-level YANG data model is for the I2NSF NSF-Facing Interface . 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. 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 Policy Data Extractor, Policy Attribute Mapper, and Policy Constructor.

Policy Data Extractor extracts attributes related to a security policy from a high-level security policy XML file that is delivered from an I2NSF User to a Security Controller . Policy Attribute 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). Policy Constructor constructs a low-level security policy XML file that is delivered from the Security Controller to an appropriate NSF .

The I2NSF framework is weak to both an inside 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. . To detect the malicious activity of either an insider attacker with its DMS or a supply chain attacker with its compromised DMS, a security audit system is required for the I2NSF framework. For this audit service in the I2NSF framework, a decentralized security audit system (e.g., blockchain ) is required. This audit system can facilitate the non-repudiation of configuration commands and monitoring data generated in the I2NSF framework. A security audit system has four main objectives such as follows: To check the existence of a security policy, a management system and its procedures; To identify and understand the existing vulnerabilities and risks of a supply chain attacker; To review existing security controls on operational, administrative and managerial issues; To provide recommendations and corrective actions for further improvement.

| Audit | | | ^ | System | +--------------+--------------+ | |(e.g., Blockchain)| | NSF-Facing Interface | +---------+--------+ | | ^ Low-level Security Policy | | | | | V | | +--------------+--------------+ | +--------+-------+ | NSF(s) | | | I2NSF Analyzer | | +------------+ | | +-----------------------------+ +----------------+ ]]>

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 (e.g., Blockchain) as transactions. The security audit system can analyze the reported activities from the I2NSF components to detect malicious activities such as supply chain attack. In order to determine a minimum set of controls required to reduce the risks from a supply chain attacker, 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.

The same security considerations for the I2NSF framework are applicable to this document. The development and introduction of I2NSF Analyzer in the I2NSF Framework will create new security concerns that have to be anticipated at the design and specification time. The usage of machine learning to analyze the data add a risk of its model to be attacked (e.g., adversarial attack) and can result in a bad security policy being deployed.

This document does not require any IANA actions.

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, 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: 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-02: This version is updated to fix the typos and clarify the text explaining Policy Attribute Mapper. Add a new Security Consideration for machine learning usage to produce a security policy.