An Information Model for the Monitoring of Network Security Functions (NSF)

According to , the interface provided by a NSF (e.g., FW, IPS, Anti-DDOS, or Anti-Virus function) to administrative entities (e.g., NMS, security controller) for configuring security function in the NSF and monitoring the NSF is referred to as a “I2NSF NSF-Facing Interface”. The monitoring part of it is meant to acquire vital information about the NSF via, e.g. notifications, events, records, counters. The monitoring of the NSF plays a very important role in the overall security framework if done in a timely and comprehensive way. The monitoring information generated by a NSF can very well be an early indication of malicious activity, or anomalous behavior, or a potential sign of denial of service attacks. This draft proposes a comprehensive NSF monitoring information model that provides visibility into NSFs. This document will not go into the design details of NSF-Facing Interfaces. Instead, this draft is focused on specifying the information and illustrates the methods that enable a NSF to provide the information required in order to be monitored in a scalable and efficient way via the NSF-Facing Interface. The information model for monitoring presented in this document is a complement to the information model for the security policy provisioning part of the NSF-Facing Interface specified in .

The key words “MUST”, “MUST NOT”, “REQUIRED”, “SHALL”, “SHALL NOT”, “SHOULD”, “SHOULD NOT”, “RECOMMENDED”, “MAY”, and “OPTIONAL” in this document are to be interpreted as described in .

This document uses the terms defined in .

As mentioned earlier, monitoring plays a very critical role in the overall security framework. The monitoring of the NSF provides very valuable information to the security controller in maintaining the provisioned security posture. Besides this, there are various other reasons to monitor the NSFs as listed below: The security administrator can configure a policy that is triggered on a specific event happened in the NSF or the network. The security controller would monitor for the specified event and once it happens, it configures additional security functions as per the policy. The events triggered by NSFs as a result of security policy violation can be used by SIEM to detect any suspicious activity. The events and activity logs from NSFs can be used to build advanced analytics such as behavior and predictive to improve the security posture. The security controller can use events from the NSF for achieving high availability. It can take corrective actions such as restarting a failed NSF, horizontally scaling the NSF etc. The events and activity logs from the NSF can aid in debugging and root cause analysis of an operational issue. The activity logs from the NSF can be used to build historical data for operational and business reasons.

In order to maintain a strong security posture, it is not only necessary to configure NSF security policies but also to continuously monitor NSF by consuming acquirable observable information. This enables security admins to assess what is happening in the network timely. It is not possible to block all the internal and external threats based on static security posture. To achieve this goal, a very dynamic posture with constant visibility is required. This draft defines a set of information elements (and their scope) that can be acquired from NSF and can be used as monitoring information. In essence, these types of monitoring information can be leveraged to support constant visibility on multiple levels of granularity and can be consumed by corresponding functions. Three basic domains about the monitoring of information originating from a system entity or a NSF are highlighted in this document. Retention and Emission Notifications and Events Unsolicited Poll and Solicited Push The Alarm Management Framework in defines an Event as “something that happens which may be of interest. A fault, a change in status, crossing a threshold, or an external input to the system, for example.” In the I2NSF domain, I2NSF events are created and the scope of the Alarm Management Framework Events is still applicable due to its broad definition. The model presented in this document elaborates on the work-flow of creating I2NSF events in the context of NSF monitoring and on how initial I2NSF events are created. As with I2NSF components, every generic system entity can include a set of capabilities that creates information about the context, composition, configuration, state or behavior of that system entity. This information is intended to be provided to other consumers of informations—and in the scope of this document, to monitor that information in an automated fashion.

Typically, a system entity populates standardized interface, such as SNMP, NETCONF, RESTCONF or CoMI to provide and emit created information directly via NSF-Facing Interfaces . Alternatively, the created information is retained inside the system entity (or hierarchy of system entities in a composite device) via records or counters that are not exposed directly via NSF-Facing Interfaces. Information emitted via standardized interfaces can be consumed by an I2NSF Agent that includes the capability to consume information not only via I2NSF Interfaces but also via interfaces complementary to the standardized interfaces a generic system entity provides. Information retained on a system entity requires a corresponding I2NSF Agent to access aggregated records of information, typically in the form of logfiles or databases. There are ways to aggregate records originating from different system entities over a network, for examples via Syslog or Syslog over TCP . But even if records are conveyed, the result is the same kind of retention in form of a bigger aggregate of records on another system entity. An I2NSF Agent is required to process fresh records created by I2NSF Functions in order to provide them to other I2NSF Components via corresponding I2NSF Interfaces timely. This process is effectively based on homogenizing functions that can access and convert specific kinds of records into information that can be provided and emitted via I2NSF interfaces. Retained or emitted, the information required to support monitoring processes has to be processed by an I2NSF Agent at some point in the work-flow. Typical locations of these I2NSF Agents are: a system entity that creates the information a system entity that retains an aggregation of records an I2NSF Component that includes the capabilities of using standardized interfaces provided by other system entities that are not I2NSF Components an I2NSF Component that creates the information

A specific task of I2NSF Agents is to process I2NSF Policy Rules . Rules are composed of three clauses: Events, Conditions, and Actions. In consequence, an I2NSF Event is required to trigger an I2NSF Policy Rule. “An I2NSF Event is defined as any important occurrence in time of a change in the system being managed, and/or in the environment of the system being managed.” , which aligns well with the generic definition of Event from . The model illustrated in this document introduces a complementary type of information that can be conveyed—notification. An occurrence of a change of context, composition, configuration, state or behavior of a system entity that can be directly or indirectly observed by an I2NSF Agent and can be used as input for an event-clause in I2NSF Policy Rules. A notification is similar to an I2NSF Event with the exception that it is created by a system entity that is not an I2NSF Component and that its importances is yet to be assessed. Semantically, a notification is not an I2NSF Event in the context of I2NSF, although they can potentially use the exact same information or data model. In respect to , a Notification is a specific subset of events, because they convey information about “something that happens which may be of interest”. In consequence, Notifications can contain information with very low expressiveness or relevance. Hence, additional post-processing functions, such as aggregation, correlation or simple anomaly detection, might have to be employed to satisfy a level of expressiveness that is required for an event-clause of an I2NSF Policy Rule. It is important to note that the consumer of a notification (the observer) assesses the importance of a notification and not the producer. The producer can include metadata in a notification that supports the observer in assessing the importance (even metadata about severity), but the deciding entity is an I2NSF Agent.

The freshness of the monitored information depends on the acquisition method. Ideally, an I2NSF Agent is accessing every relevant information about the I2NSF Component and is emitting I2NSF Events to a monitoring NSF timely. Publication of events via a pubsub/broker model, peer-2-peer meshes, or static defined channels are only a few examples on how a solicited push of I2NSF Events can be facilitated. The actual mechanic implemented by an I2NSF Component is out of the scope of this document. Often, corresponding management interfaces have to be queried in intervals or on-demand if required by an I2NSF Policy rule. In some cases, a collection of information has to be conducted via login mechanics provided by a system entity. Accessing records of information via this kind of unsolicited polls can introduce a significant latency in regard to the freshness of the monitored information. The actual definition of intervals implemented by an I2NSF Component is also out of scope of this document.

Unlike information emitted via notifications and events, records do not require immediate attention from an analyst but may be useful for visibility and retroactive cyber forensic. Depending on the record format, there are different qualities in regard to structure and detail. Records are typically stored in logfiles or databases on a system entity or NSF. Records in the form of logfiles usually include less structures but potentially more detailed information in regard to changes of an system entity’s characteristics. In contrast, databases often use more strict schemas or data models, therefore enforcing a better structure, but inhibit storing information that do not match those models (‘closed world assumption’). Records can be continuously processed by I2NSF Agents that act as I2NSF Producer and emit events via functions specifically tailored to a certain type of record. Typically, records are information generated by NSF or system entity about their operational and informational data, or various changes in system characteristics, such as user activities, network/traffic status, network activity, etc. They are important for debugging, auditing and security forensic. A specific representation of continuous value changes of information elements that potentially occur in high frequency. A prominent example are network interface counters, e.g. PDU amount or byte amount, drop counters, error counters etc. Counters are useful in debugging and visibility into operational behavior of the NSF. An I2NSF Agent that observes the progression of counters can act as an I2NSF Producer and emit events in respect to I2NSF Policy Rules.

As per the use cases of NSF monitoring data, information needs to be conveyed to various I2NSF Consumers based on requirements imposed by I2NSF Capabilities and work-flows. There are multiple aspects to be considered in regard to emission of monitoring information to requesting parties as listed below: Pull-Push Model: A set of data can be pushed by a NSF to the requesting party or pulled by the requesting party from a NSF. Specific types of information might need both the models at the same time if there are multiple I2NSF Consumers with varying requirements. In general, any I2NSF Event including a high severity assessment is considered to be of great importance and should be processed as soon as possible (push-model). Records, in contrast, are typically not as critical (pull-model). The I2NSF Architecture does not mandate a specific scheme for each type of information and is therefore out of scope of this document. Pub-Sub Model: In order for an I2NSF Provider to push monitoring information to multiple appropriate I2NSF Consumers, a subscription can be maintained by both I2NSF Components. Discovery of available monitoring information can be supported by an I2NSF Controller that takes on the role of a broker and therefore includes I2NSF Capabilities that support registration. Export Frequency: Monitoring information can be emitted immediately upon generation by a NSF to requesting I2NSF Consumers or can be pushed periodically. The frequency of exporting the data depends upon its size and timely usefulness. It is out of the scope of I2NSF and left to each NSF implementation. Authentication: There may be a need for authentication between I2NSF Producer of monitoring information and corresponding I2NSF Consumer to ensure that critical information remains confidential. Authentication in the scope of I2NSF can also require a corresponding content authorization. This may be necessary, for example, if a NSF emits monitoring information to I2NSF Consumer outside its administrative domain. The I2NSF Architecture does not mandate when and how specific authentication has to be implemented. Data-Transfer Model: Monitoring information can be pushed by NSF using a connection-less model that does require a persistent connection or streamed over a persistent connection. An appropriate model depends on the I2NSF Consumer requirements and the semantics of the information to be conveyed. Data Model and Interaction Model for Data in Motion: There are a lot of transport mechanisms such as IP, UDP, TCP. There are also open source implementations for specific set of data such as systems counter, e.g. IPFIX or NetFlow . The I2NSF does not mandate any specific method for a given data set, it is up to each implementation.

As explained in the above section, there is a wealth of data available from the NSF that can be monitored. Firstly, there must be some general information with each monitoring message sent from an NSF that helps consumer in identifying meta data with that message, which are listed as below: message_version: Indicate the version of the data format and is a two-digit decimal numeral starting from 01 message_type: Event, Alert, Alarm, Log, Counter, etc time_stamp: Indicate the time when the message is generated vendor_name: The name of the NSF vendor NSF_name: The name (or IP) of the NSF generating the message Module_name: The module name outputting the message Severity: Indicates the level of the logs. There are total eight levels, from 0 to 7. The smaller the numeral is, the higher the severity is.

This section covers the additional information associated with the system messages. The extended information model is only for the structured data such as alarm. Any unstructured data is specified with basic information model only. [Editors’ note]: This section remains the same as -02 version, although the classification of the monitoring data has been changed from -02 version. The new inconsistency will be addressed in next verion.

The following information should be included in a Memory Alarm: event_name: ‘MEM_USAGE_ALARM’ module_name: Indicate the NSF module responsible for generating this alarm usage: specifies the amount of memory used threshold: The threshold triggering the alarm severity: The severity of the alarm such as critical, high, medium, low message: ‘The memory usage exceeded the threshold’

The following information should be included in a CPU Alarm: event_name: ‘CPU_USAGE_ALARM’ usage: Specifies the amount of CPU used threshold: The threshold triggering the event severity: The severity of the alarm such as critical, high, medium, low message: ‘The CPU usage exceeded the threshold’

The following information should be included in a Disk Alarm: event_name: ‘DISK_USAGE_ALARM’ usage: Specifies the amount of disk space used threshold: The threshold triggering the event severity: The severity of the alarm such as critical, high, medium, low message: ‘The disk usage exceeded the threshold’

The following information should be included in a Hardware Alarm: event_name: ‘HW_FAILURE_ALARM’ component_name: Indicate the HW component responsible for generating this alarm threshold: The threshold triggering the alarm severity: The severity of the alarm such as critical, high, medium, low message: ‘The HW component has failed or degraded’

The following information should be included in a Interface Alarm: event_name: ‘IFNET_STATE_ALARM’ interface_Name: The name of interface interface_state: ‘UP’, ‘DOWN’, ‘CONGESTED’ threshold: The threshold triggering the event severity: The severity of the alarm such as critical, high, medium, low message: ‘Current interface state’

The following information should be included in this event: event_name: ‘ACCESS_DENIED’ user: Name of a user group: Group to which a user belongs login_ip_address: Login IP address of a user authentication_mode: User authentication mode. e.g., Local Authentication, Third-Party Server Authentication, Authentication Exemption, SSO Authentication message: ‘access denied’

The following information should be included in this event: event_name: ‘CONFIG_CHANGE’ user: Name of a user group: Group to which a user belongs login_ip_address: Login IP address of a user authentication_mode: User authentication mode. e.g., Local Authentication, Third-Party Server Authentication, Authentication Exemption, SSO Authentication message: ‘Configuration modified’

Access logs record administrators’ login, logout, and operations on the device. By analyzing them, security vulnerabilities can be identified. The following information should be included in operation report: Administrator: Administrator that operates on the device login_ip_address: IP address used by an administrator to log in login_mode: Specifies the administrator logs in mode e.g. root, user operation_type: The operation type that the administrator execute, e.g., login, logout, configuration, etc result: Command execution result content: Operation performed by an administrator after login.

Running reports record the device system’s running status, which is useful for device monitoring. The following information should be included in running report: system_status: The current system’s running status CPU_usage: Specifies the CPU usage memory_usage: Specifies the memory usage disk_usage: Specifies the disk usage disk_left: Specifies the available disk space left session_number: Specifies total concurrent sessions process_number: Specifies total number of system processes in_traffic_rate: The total inbound traffic rate in pps out_traffic_rate: The total outbound traffic rate in pps in_traffic_speed: The total inbound traffic speed in bps out_traffic_speed: The total outbound traffic speed in bps

User activity logs provide visibility into users’ online records (such as login time, online/lockout duration, and login IP addresses) and the actions users perform. User activity reports are helpful to identify exceptions during user login and network access activities. user: Name of a user group: Group to which a user belongs login_ip_address: Login IP address of a user authentication_mode: User authentication mode. e.g., Local Authentication, Third-Party Server Authentication, Authentication Exemption, SSO Authentication access_mode: User access mode. e.g., PPP, SVN, LOCAL online_duration: Online duration lockout_duration: Lockout duration type: User activities. e.g., Successful User Login, Failed Login attempts, User Logout, Successful User Password Change, Failed User Password Change, User Lockout, User Unlocking, Unknown cause: Cause of a failed user activity

Interface counters provide visibility into traffic into and out of NSF, bandwidth usage. interface_name: Network interface name configured in NSF in_total_traffic_pkts: Total inbound packets out_total_traffic_pkts: Total outbound packets in_total_traffic_bytes: Total inbound bytes out_total_traffic_bytes: Total outbound bytes in_drop_traffic_pkts: Total inbound drop packets out_drop_traffic_pkts: Total outbound drop packets in_drop_traffic_bytes: Total inbound drop bytes out_drop_traffic_bytes: Total outbound drop bytes in_traffic_ave_rate: Inbound traffic average rate in pps in_traffic_peak_rate: Inbound traffic peak rate in pps in_traffic_ave_speed: Inbound traffic average speed in bps in_traffic_peak_speed: Inbound traffic peak speed in bps out_traffic_ave_rate: Outbound traffic average rate in pps out_traffic_peak_rate: Outbound traffic peak rate in pps out_traffic_ave_speed: Outbound traffic average speed in bps out_traffic_peak_speed: Outbound traffic peak speed in bps.

The following information should be included in a DDoS Event: event_name: ‘SEC_EVENT_DDoS’ sub_attack_type: Any one of Syn flood, ACK flood, SYN-ACK flood, FIN/RST flood, TCP Connection flood, UDP flood, Icmp flood, HTTPS flood, HTTP flood, DNS query flood, DNS reply flood, SIP flood, and etc. dst_ip: The IP address of a victum under attack dst_port: The port numbers that the attrack traffic aims at. start_time: The time stamp indicating when the attack started end_time: The time stamp indicating when the attack ended. If the attack is still undergoing when sending out the alarm, this field can be empty. attack_rate: The PPS of attack traffic attack_speed: the bps of attack traffic rule_id: The ID of the rule being triggered rule_name: The name of the rule being triggered profile: Security profile that traffic matches.

The following information should be included in a Session Table Event: event_name: ‘SESSION_USAGE_HIGH’ current: The number of concurrent sessions max: The maximum number of sessions that the session table can support threshold: The threshold triggering the event message: ‘The number of session table exceeded the threshold’

The following information should be included in a Virus Event: event_Name: ‘SEC_EVENT_VIRUS’ virus_type: Type of the virus, e.g., trojan, worm, macro Virus type virus_name dst_ip: The destination IP address of the packet where the virus is found src_ip: The source IP address of the packet where the virus is found src_port: The source port of the packet where the virus is found dst_port: The destination port of the packet where the virus is found src_zone: The source security zone of the packet where the virus is found dst_zone: The destination security zone of the packet where the virus is found file_type: The type of the file where the virus is hided within file_name: The name of the file where the virus is hided within virus_info: The brief introduction of virus raw_info: The information describing the packet triggering the event. rule_id: The ID of the rule being triggered rule_name: The name of the rule being triggered profile: Security profile that traffic matches.

The following information should be included in a Intrustion Event: event_name: The name of event: ‘SEC_EVENT_Intrusion’ sub_attack_type: Attack type, e.g., brutal force, buffer overflow src_ip: The source IP address of the packet dst_ip: The destination IP address of the packet src_port:The source port number of the packet dst_port: The destination port number of the packet src_zone: The source security zone of the packet dst_zone: The destination security zone of the packet protocol: The employed transport layer protocol, e.g.,TCP, UDP app: The employed application layer protocol, e.g.,HTTP, FTP rule_id: The ID of the rule being triggered rule_name: The name of the rule being triggered profile: Security profile that traffic matches intrusion_info: Simple description of intrusion raw_info: The information describing the packet triggering the event.

The following information should be included in a Botnet Event: event_name: the name of event: ‘SEC_EVENT_Botnet’ botnet_name: The name of the detected botnet src_ip: The source IP address of the packet dst_ip: The destination IP address of the packet src_port: The source port number of the packet dst_port: The destination port number of the packet src_zone: The source security zone of the packet dst_zone: The destination security zone of the packet protocol: The employed transport layer protocol, e.g.,TCP, UDP app: The employed application layer protocol, e.g.,HTTP, FTP role: The role of the communicating parties within the botnet: the packet from zombie host to the attacker The packet from the attacker to the zombie host The packet from the IRC/WEB server to the zombie host The packet from the zombie host to the IRC/WEB server The packet from the attacker to the IRC/WEB server The packet from the IRC/WEB server to the attacker The packet from the zombie host to the victim botnet_info: Simple description of Botnet rule_id: The ID of the rule being triggered rule_name: The name of the rule being triggered profile: Security profile that traffic matches raw_info: The information describing the packet triggering the event.

The following information should be included in a Web Attack Alarm: event_name: the name of event: ‘SEC_EVENT_WebAttack’ sub_attack_type: Concret web attack type, e.g., sql injection, command injection, XSS, CSRF src_ip: The source IP address of the packet dst_ip: The destination IP address of the packet src_port: The source port number of the packet dst_port: The destination port number of the packet src_zone: The source security zone of the packet dst_zone: The destination security zone of the packet req_method: The method of requirement. For instance, ‘PUT’ or ‘GET’ in HTTP req_url: Requested URL url_category: Matched URL category filtering_type: URL filtering type, e.g., Blacklist, Whitelist, User-Defined, Predefined, Malicious Category, Unknown rule_id: The ID of the rule being triggered rule_name: The name of the rule being triggered profile: Security profile that traffic matches.

Besides the fields in an DDoS Alarm, the following information should be included in a DDoS Logs: attack_type: DDoS attack_ave_rate: The average pps of the attack traffic within the recorded time attack_ave_speed: The average bps of the attack traffic within the recorded time attack_pkt_num: The number attack packets within the recorded time attack_src_ip: The source IP addresses of attack traffics. If there are a large amount of IP addresses, then pick a certain number of resources according to different rules. action: Actions against DDoS attacks, e.g., Allow, Alert, Block, Discard, Declare, Block-ip, Block-service.

Besides the fields in an Virus Alarm, the following information should be included in a Virus Logs: attack_type: Virus protocol: The transport layer protocol app: The name of the application layer protocol times: The time of detecting the virus action: The actions dealing with the virus, e.g., alert, block os: The OS that the virus will affect, e.g., all, android, ios, unix, windows

Besides the fields in an Intrusion Alarm, the following information should be included in a Intrusion Logs: attack_type: Intrusion times: The times of intrusions happened in the recorded time os: The OS that the intrusion will affect, e.g., all, android, ios, unix, windows action: The actions dealing with the intrusions, e.g., e.g., Allow, Alert, Block, Discard, Declare, Block-ip, Block-service attack_rate: NUM the pps of attack traffic attack_speed: NUM the bps of attack traffic

Besides the fields in an Botnet Alarm, the following information should be included in a Botnet Logs: attack_type: Botnet botnet_pkt_num:The number of the packets sent to or from the detected botnet action: The actions dealing with the detected packets, e.g., Allow, Alert, Block, Discard, Declare, Block-ip, Block-service, etc os: The OS that the attack aiming at, e.g., all, android, ios, unix, windows, etc.

DPI Logs provide statistics on uploaded and downloaded files and data, sent and received emails, and alert and block records on websites. It’s helpful to learn risky user behaviors and why access to some URLs is blocked or allowed with an alert record. type: DPI action types. e.g., File Blocking, Data Filtering, Application Behavior Control file_name: The file name file_type: The file type src_zone: Source security zone of traffic dst_zone: Destination security zone of traffic src_region: Source region of the traffic dst_region: Destination region of the traffic src_ip: Source IP address of traffic src_user: User who generates traffic dst_ip: Destination IP address of traffic src_port: Source port of traffic dst_port: Destination port of traffic protocol: Protocol type of traffic app: Application type of traffic policy_id: Security policy id that traffic matches policy_name: Security policy name that traffic matches action: Action defined in the file blocking rule, data filtering rule, or application behavior control rule that traffic matches.

Vulnerability scanning logs record the victim host and its related vulnerability information that should to be fixed. the following information should be included in the report: victim_ip: IP address of the victim host which has vulnerabilities vulnerability_id: The vulnerability id vulnerability_level: The vulnerability level. e.g., high, middle, low OS: The operating system of the victim host service: The service which has vulnerabillity in the victim host protocol: The protocol type. e.g., TCP, UDP port: The port number vulnerability_info: The information about the vulnerability fix_suggestion: The fix suggestion to the vulnerability.

Besides the fields in an Web Attack Alarm, the following information should be included in a Web Attack Report: attack_type: Web Attack rsp_code: Response code req_clientapp: The client application req_cookies: Cookies req_host: The domain name of the requested host raw_info: The information describing the packet triggering the event.

Firewall counters provide visibility into traffic signatures, bandwidth usage, and how the configured security and bandwidth policies have been applied. src_zone: Source security zone of traffic dst_zone: Destination security zone of traffic src_region: Source region of the traffic dst_region: Destination region of the traffic src_ip: Source IP address of traffic src_user: User who generates traffic dst_ip: Destination IP address of traffic src_port: Source port of traffic dst_port: Destination port of traffic protocol: Protocol type of traffic app: Application type of traffic policy_id: Security policy id that traffic matches policy_name: Security policy name that traffic matches in_interface: Inbound interface of traffic out_interface: Outbound interface of traffic total_traffic: Total traffic volume in_traffic_ave_rate: Inbound traffic average rate in pps in_traffic_peak_rate: Inbound traffic peak rate in pps in_traffic_ave_speed: Inbound traffic average speed in bps in_traffic_peak_speed: Inbound traffic peak speed in bps out_traffic_ave_rate: Outbound traffic average rate in pps out_traffic_peak_rate: Outbound traffic peak rate in pps out_traffic_ave_speed: Outbound traffic average speed in bps out_traffic_peak_speed: Outbound traffic peak speed in bps.

Policy Hit Counters record the security policy that traffic matches and its hit count. It can check if policy configurations are correct. src_zone: Source security zone of traffic dst_zone: Destination security zone of traffic src_region: Source region of the traffic dst_region: Destination region of the traffic src_ip: Source IP address of traffic src_user: User who generates traffic dst_ip: Destination IP address of traffic src_port: Source port of traffic dst_port: Destination port of traffic protocol: Protocol type of traffic app: Application type of traffic policy_id: Security policy id that traffic matches policy_name: Security policy name that traffic matches hit_times: The hit times that the security policy matches the specified traffic.

This document makes no request of IANA. Note to RFC Editor: this section may be removed on publication as an RFC.

The monitoring information of NSF should be protected by the secure communication channel, to ensure its confidentiality and integrity. In another side, the NSF and security controller can all be faked, which lead to undesireable results, i.e., leakage of NSF’s important operational information, faked NSF sending false information to mislead security controller. The mutual authentication is essential to protected against this kind of attack. The current mainstream security technologies (i.e., TLS, DTLS, IPSEC, X.509 PKI) can be employed approriately to provide the above security functions. In addition, to defend against the DDoS attack caused by a lot of NSFs sending massive monitoring information to the security controller, the rate limiting or similar mechanisms should be considered in NSF and security controller, whether in advance or just in the process of DDoS attack.