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draft-netana-opsawg-nmrg-network-anomaly-semantics-00.xml
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<?xml version="1.0" encoding="US-ASCII"?>
<!DOCTYPE rfc SYSTEM "rfc2629.dtd">
<?rfc toc="yes"?>
<?rfc tocompact="yes"?>
<?rfc tocdepth="2"?>
<?rfc tocindent="yes"?>
<?rfc symrefs="yes"?>
<?rfc sortrefs="yes"?>
<?rfc comments="yes"?>
<?rfc inline="yes"?>
<?rfc compact="yes"?>
<?rfc subcompact="no"?>
<rfc category="exp"
docName="draft-netana-opsawg-nmrg-network-anomaly-semantics-00"
ipr="trust200902">
<front>
<title abbrev="Network Anomaly Semantics">Semantic Metadata Annotation for
Network Anomaly Detection</title>
<author fullname="Thomas Graf" initials="T" surname="Graf">
<organization>Swisscom</organization>
<address>
<postal>
<street>Binzring 17</street>
<city>Zurich</city>
<code>8045</code>
<country>Switzerland</country>
</postal>
<email>[email protected]</email>
</address>
</author>
<author fullname="Wanting Du" initials="W" surname="Du">
<organization>Swisscom</organization>
<address>
<postal>
<street>Binzring 17</street>
<city>Zurich</city>
<code>8045</code>
<country>Switzerland</country>
</postal>
<email>[email protected]</email>
</address>
</author>
<author fullname="Alex Huang Feng" initials="A." surname="Huang Feng">
<organization>INSA-Lyon</organization>
<address>
<postal>
<street/>
<city>Lyon</city>
<region/>
<code/>
<country>France</country>
</postal>
<phone/>
<facsimile/>
<email>[email protected]</email>
<uri/>
</address>
</author>
<date day="23" month="October" year="2023"/>
<abstract>
<t>This document explains why and how semantic metadata annotation helps
to test and validate outlier detection, supports supervised and
semi-supervised machine learning development and make anomalies for
humans apprehensible. The proposed semantics uniforms the network
anomaly data exchange between and among operators and vendors to improve
their network outlier detection systems.</t>
</abstract>
<note title="Requirements Language">
<t>The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
"SHOULD", "SHOULD NOT", "RECOMMENDED", "NOT RECOMMENDED", "MAY", and
"OPTIONAL" in this document are to be interpreted as described in BCP 14
<xref target="RFC2119"/> <xref target="RFC8174"/> when, and only when,
they appear in all capitals, as shown here.</t>
</note>
</front>
<middle>
<section anchor="Introduction" title="Introduction">
<t><xref target="Ahf23">Network Anomaly Detection Architecture</xref>
provides an overall introduction into how anomaly detection is being
applied into the IP network domain and which operational data is needed.
It approaches the problem space by automating what a Network Engineer
would normally do when veryfing a network connectivity service. Monitor
from different network plane perspectives to understand wherever one
network plane affects another negatively.</t>
<t>In order to fine tune outlier detection, the results provided as
analytical data need to be reviewed by a Network Engineer. Keeping the
human out of the monitoring but still involving him in the alert
verification loop.</t>
<t>This document describes what information is needed to understand the
output of the outlier detection for a Network Engineer, but also at the
same time is semantically structured that it can be used for outlier
detection testing by comparing the results systematically and set a
baseline for supervised machine learning which requires labeled
operational data.</t>
</section>
<section anchor="Outlier_Detection" title="Outlier Detection">
<t>Outlier Detection, also known as anomaly detection, describes a
systematic approach to identify rare data points deviating significantly
from the majority. Outliers are commonly classified in three
categories:</t>
<dl>
<dt>Global outliers:</dt>
<dd>A data point is considered a global outlier if its value is far
outside the entirety of a data set. For example, an average dropped
packet count is between 0 and 10 per minute during a one week
observation and the observed global outlier was 100000 packets.</dd>
</dl>
<dl>
<dt>Contextual outliers:</dt>
<dd>A data point is considered a contextual outlier if its value
significantly deviates from the rest of the data points in the same
time series context. For example, the forwarded packet volume in a
timeseries are changing during the time of the day like an oscillation
curve, where the observed contextual packet volume outlier is outside
the oscillation curve at that moment in time. At another time the same
value could be considered normal.</dd>
</dl>
<dl>
<dt>Collective outliers:</dt>
<dd>A subset of data points within a data set is considered anomalous
if those values as a collection deviate significantly from the entire
data set, but the values of the individual data points are not
themselves anomalous in either a contextual or global sense. In
Network Telemetry time series, one way this can manifest is that the
amount of network path and interface state changes matches the time
range when the forwarded packet volume decreases as a group.</dd>
</dl>
<t>For each outlier a score between 0 and 1 is being calculated. The
higher the value, the higher the probability that the observed data
point is an outlier. <xref target="VAP09">Anomaly detection: A
survey</xref> gives additional details on anomaly detection and its
types.</t>
</section>
<section anchor="Data_Mesh" title="Data Mesh">
<t>The <xref target="Deh22">Data Mesh</xref> Architecture distinguishes
between operational and analytical data. Operational data refers to
collected data from operational systems. While analytical data refers to
insights gained from operational data.</t>
<t>In terms of network observability, semantics of operational network
metrics are defined by IETF and are categorized as described in the
Network Telemetry Framework <xref target="RFC9232"/> in the following
three different network planes:</t>
<dl>
<dt>Management Plane:</dt>
<dd>Time series data describing the state changes and statistics of a
network node and its components. For example, Interface state and
statistics modelled in ietf-interfaces.yang <xref
target="RFC8343"/></dd>
</dl>
<dl>
<dt>Control Plane:</dt>
<dd>Time series data describing the state and state changes of network
reachability. For example, BGP VPNv6 unicast updates and withdrawals
exported in BGP Monitoring Protocol (BMP) <xref target="RFC7854"/> and
modeled in BGP <xref target="RFC4364"/></dd>
</dl>
<dl>
<dt>Forwarding Plane:</dt>
<dd>Time series data describing the forwarding behavior of packets and
its data-plane context. For example, dropped packet count modelled in
IPFIX entity forwardingStatus(IE89) <xref target="RFC7270"/> and
packetDeltaCount(IE2) <xref target="RFC5102"/> and exportet with IPFIX
<xref target="RFC7011"/>.</dd>
</dl>
<t>In terms of network observability, semantics of analytical data
refers to incident notifications or service level indicators. For
example the incident notification described in Section 7.2 of <xref
target="I-D.feng-opsawg-incident-management"/>, the health status and
symptoms described in the Service Assurance Intend Based Networking
<xref target="RFC9418"/> or the precision availability metrics defined
in <xref target="I-D.ietf-ippm-pam"/> or network anomalies and its
symptoms as described in this document.</t>
</section>
<section anchor="Observed_Symptoms" title="Observed Symptoms">
<t>In this section observed network symptoms are specified and
categorized according to the following scheme:</t>
<dl>
<dt>Action:</dt>
<dd>
<t>Which action the network node performed for a packet in the
Forwarding Plane, a path or adjancency in the Control Plane or state
or statistical changes in the Management Plane. For Forwarding Plane
we distinguish between missing, where the drop occured outside the
measured network node, drop and on-path delay, which was measured on
the network node. For control-plane we distinguish between
reachability, which refers to a change in the routing or forwarding
information base (RIB/FIB) and adjcacency which refers to a change
in peering or link-layer resolution. For Management Plane we refer
to state or statistical changes on interfaces.</t>
</dd>
</dl>
<dl>
<dt>Reason:</dt>
<dd>
<t>For each action one or more reasons describinging why this action
was used. For Drops in Forwarding Plane we distinguish between
Unreachable because network layer reachability information was
missing, administered because an administrator configured a rule
preventing the forwarding for this packet and Corrupt where the
network node was unable to determine where to forward to due to
packet, software or hardware error. For On-Path Delay we distinguish
between Minimum, Average and Maximum Delay for a given Flow.</t>
</dd>
</dl>
<dl>
<dt>Relation:</dt>
<dd>
<t>For each reason one or more relation describe the cause why the
action was chosen. These reason could relate network plane entity, a
packet, control-plane or node administered instruction.</t>
</dd>
</dl>
<t><xref target="symptom_forwarding_plane_actions_table"/> consolidates
for the forwarding plane a list of common symptoms with their actions,
reasons and relations.</t>
<table align="center" anchor="symptom_forwarding_plane_actions_table">
<name slugifiedName="symptom_forwarding_plane_actions">Describing
Symptoms and their Actions, Reason and Relation for Forwarding
Plane</name>
<thead>
<tr>
<th align="left" colspan="1" rowspan="1">Action</th>
<th align="left" colspan="1" rowspan="1">Reason</th>
<th align="left" colspan="1" rowspan="1">Relation</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" colspan="1" rowspan="1">Missing</td>
<td align="left" colspan="1" rowspan="1">Previous</td>
<td align="left" colspan="1" rowspan="1">Time</td>
</tr>
<tr>
<td align="left" colspan="1" rowspan="1">Drop</td>
<td align="left" colspan="1" rowspan="1">Unreachable</td>
<td align="left" colspan="1" rowspan="1">next-hop</td>
</tr>
<tr>
<td align="left" colspan="1" rowspan="1">Drop</td>
<td align="left" colspan="1" rowspan="1">Unreachable</td>
<td align="left" colspan="1" rowspan="1">link-layer</td>
</tr>
<tr>
<td align="left" colspan="1" rowspan="1">Drop</td>
<td align="left" colspan="1" rowspan="1">Unreachable</td>
<td align="left" colspan="1" rowspan="1">Time To Life expired</td>
</tr>
<tr>
<td align="left" colspan="1" rowspan="1">Drop</td>
<td align="left" colspan="1" rowspan="1">Unreachable</td>
<td align="left" colspan="1" rowspan="1">Fragmentation needed and
Don't Fragment set</td>
</tr>
<tr>
<td align="left" colspan="1" rowspan="1">Drop</td>
<td align="left" colspan="1" rowspan="1">Administered</td>
<td align="left" colspan="1" rowspan="1">Access-List</td>
</tr>
<tr>
<td align="left" colspan="1" rowspan="1">Drop</td>
<td align="left" colspan="1" rowspan="1">Administered</td>
<td align="left" colspan="1" rowspan="1">Unicast Reverse Path
Forwarding</td>
</tr>
<tr>
<td align="left" colspan="1" rowspan="1">Drop</td>
<td align="left" colspan="1" rowspan="1">Administered</td>
<td align="left" colspan="1" rowspan="1">Discard Route</td>
</tr>
<tr>
<td align="left" colspan="1" rowspan="1">Drop</td>
<td align="left" colspan="1" rowspan="1">Administered</td>
<td align="left" colspan="1" rowspan="1">Policed</td>
</tr>
<tr>
<td align="left" colspan="1" rowspan="1">Drop</td>
<td align="left" colspan="1" rowspan="1">Administered</td>
<td align="left" colspan="1" rowspan="1">Shaped</td>
</tr>
<tr>
<td align="left" colspan="1" rowspan="1">Drop</td>
<td align="left" colspan="1" rowspan="1">Corrupt</td>
<td align="left" colspan="1" rowspan="1">Bad Packet</td>
</tr>
<tr>
<td align="left" colspan="1" rowspan="1">Drop</td>
<td align="left" colspan="1" rowspan="1">Corrupt</td>
<td align="left" colspan="1" rowspan="1">Bad Egress Interface</td>
</tr>
<tr>
<td align="left" colspan="1" rowspan="1">Delay</td>
<td align="left" colspan="1" rowspan="1">Min</td>
<td align="left" colspan="1" rowspan="1">-</td>
</tr>
<tr>
<td align="left" colspan="1" rowspan="1">Delay</td>
<td align="left" colspan="1" rowspan="1">Mean</td>
<td align="left" colspan="1" rowspan="1">-</td>
</tr>
<tr>
<td align="left" colspan="1" rowspan="1">Delay</td>
<td align="left" colspan="1" rowspan="1">Max</td>
<td align="left" colspan="1" rowspan="1">-</td>
</tr>
</tbody>
</table>
<t><xref target="symptom_control_plane_actions_table"/> consolidates for
the control plane a list of common symptoms with their actions, reasons
and relations.</t>
<table align="center" anchor="symptom_control_plane_actions_table">
<name slugifiedName="symptom_control_plane_actions">Describing
Symptoms and their Actions, Reason and Relation for Control
Plane</name>
<thead>
<tr>
<th align="left" colspan="1" rowspan="1">Action</th>
<th align="left" colspan="1" rowspan="1">Reason</th>
<th align="left" colspan="1" rowspan="1">Relation</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" colspan="1" rowspan="1">Reachability</td>
<td align="left" colspan="1" rowspan="1">Update</td>
<td align="left" colspan="1" rowspan="1">Imported</td>
</tr>
<tr>
<td align="left" colspan="1" rowspan="1">Reachability</td>
<td align="left" colspan="1" rowspan="1">Update</td>
<td align="left" colspan="1" rowspan="1">Received</td>
</tr>
<tr>
<td align="left" colspan="1" rowspan="1">Reachability</td>
<td align="left" colspan="1" rowspan="1">Withdraw</td>
<td align="left" colspan="1" rowspan="1">Received</td>
</tr>
<tr>
<td align="left" colspan="1" rowspan="1">Reachability</td>
<td align="left" colspan="1" rowspan="1">Withdraw</td>
<td align="left" colspan="1" rowspan="1">Peer Down</td>
</tr>
<tr>
<td align="left" colspan="1" rowspan="1">Adjacency</td>
<td align="left" colspan="1" rowspan="1">Established</td>
<td align="left" colspan="1" rowspan="1">Peer</td>
</tr>
<tr>
<td align="left" colspan="1" rowspan="1">Adjacency</td>
<td align="left" colspan="1" rowspan="1">Established</td>
<td align="left" colspan="1" rowspan="1">Link-Layer</td>
</tr>
<tr>
<td align="left" colspan="1" rowspan="1">Adjacency</td>
<td align="left" colspan="1" rowspan="1">Teared Down</td>
<td align="left" colspan="1" rowspan="1">Peer</td>
</tr>
<tr>
<td align="left" colspan="1" rowspan="1">Adjacency</td>
<td align="left" colspan="1" rowspan="1">Teared Down</td>
<td align="left" colspan="1" rowspan="1">Link-Layer</td>
</tr>
</tbody>
</table>
<t><xref target="symptom_management_plane_actions_table"/> consolidates
for the management plane a list of common symptoms with their actions,
reasons and relations.</t>
<table align="center" anchor="symptom_management_plane_actions_table">
<name slugifiedName="symptom_management_plane_actions">Describing
Symptoms and their Actions, Reason and Relation for Management
Plane</name>
<thead>
<tr>
<th align="left" colspan="1" rowspan="1">Action</th>
<th align="left" colspan="1" rowspan="1">Reason</th>
<th align="left" colspan="1" rowspan="1">Relation</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" colspan="1" rowspan="1">Interface</td>
<td align="left" colspan="1" rowspan="1">Up</td>
<td align="left" colspan="1" rowspan="1">Link-Layer</td>
</tr>
<tr>
<td align="left" colspan="1" rowspan="1">Interface</td>
<td align="left" colspan="1" rowspan="1">Down</td>
<td align="left" colspan="1" rowspan="1">Link-Layer</td>
</tr>
<tr>
<td align="left" colspan="1" rowspan="1">Interface</td>
<td align="left" colspan="1" rowspan="1">Errors</td>
<td align="left" colspan="1" rowspan="1">-</td>
</tr>
<tr>
<td align="left" colspan="1" rowspan="1">Interface</td>
<td align="left" colspan="1" rowspan="1">Discards</td>
<td align="left" colspan="1" rowspan="1">-</td>
</tr>
<tr>
<td align="left" colspan="1" rowspan="1">Interface</td>
<td align="left" colspan="1" rowspan="1">Unknown Protocol</td>
<td align="left" colspan="1" rowspan="1">-</td>
</tr>
</tbody>
</table>
</section>
<section anchor="Semantic_Metadata" title="Semantic Metadata">
<t>Metadata adds additional context to data. For instance, in networks
the software version of a network node where management plane metrics
are obtained from as described in <xref
target="I-D.claise-opsawg-collected-data-manifest"/>. Where in Semantic
Metadata the meaning or ontology of the annotated data is being
described.</t>
<section anchor="model-tree" title="Overview of the Model">
<t><xref target="anomaly-detection-semantic-metadata-tree"/> contains
the YANG tree diagram <xref target="RFC8340"/> of the
ietf-anomaly-detection-semantic-metadata module. <figure
anchor="anomaly-detection-semantic-metadata-tree"
title="YANG tree diagram for ietf-anomaly-detection-semantic-metadata">
<artwork><![CDATA[
module: ietf-anomaly-detection-semantic-metadata
]]></artwork>
</figure></t>
<t>Describe YANG module</t>
</section>
</section>
<section anchor="Security" title="Security Considerations">
<t>The security considerations.</t>
</section>
<section anchor="Acknowledgements" title="Acknowledgements">
<t>The authors would like to thank xxx for their review and valuable
comments.</t>
</section>
</middle>
<back>
<references title="Normative References">
<?rfc include='reference.RFC.2119'?>
<?rfc include='reference.RFC.8174'?>
<?rfc include='reference.RFC.8340'?>
<?rfc include='reference.RFC.9232'?>
<reference anchor="Ahf23"
target="https://anrw23.hotcrp.com/doc/anrw23-paper8.pdf">
<front>
<title>Daisy: Practical Anomaly Detection in large BGP/MPLS and
BGP/SRv6 VPN Networks</title>
<author fullname="Alex Huang Feng" initials="A."
surname="Huang Feng"/>
<date month="July" year="2023"/>
</front>
<seriesInfo name="DOI" value="10.1145/3606464.3606470"/>
<refcontent>IETF 117, Applied Networking Research
Workshop</refcontent>
</reference>
</references>
<references title="Informative References">
<?rfc include='reference.RFC.4364'?>
<?rfc include='reference.RFC.5102'?>
<?rfc include='reference.RFC.7011'?>
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<reference anchor="VAP09"
target="https://www.researchgate.net/publication/220565847_Anomaly_Detection_A_Survey">
<front>
<title>Anomaly detection: A survey</title>
<author fullname="Varun Chandola" initials="V." surname="Chandola"/>
<author fullname="Arindam Banerjee" initials="A." surname="Banerjee"/>
<author fullname="Vipin Kumar" initials="V." surname="Kumar"/>
<date month="July" year="2009"/>
</front>
<seriesInfo name="DOI" value="10.1145/1541880.1541882"/>
<refcontent>IETF 117, Applied Networking Research
Workshop</refcontent>
</reference>
<reference anchor="Deh22"
target="https://www.oreilly.com/library/view/data-mesh/9781492092384/">
<front>
<title>Data Mesh</title>
<author fullname="Zhamak Dehghani" initials="Z." surname="Dehghani"/>
<date month="March" year="2022"/>
</front>
<seriesInfo name="ISBN" value="9781492092391"/>
<refcontent>O'Reilly Media</refcontent>
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