Network Working Group F. Dressler
Internet-Draft C. Sommer
Expires: June 23, 2006 University of Erlangen
G. Muenz
University of Tuebingen
December 20, 2005
IPFIX Aggregation
<draft-dressler-ipfix-aggregation-02.txt>
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Copyright (C) The Internet Society (2005).
Abstract
IPFIX Aggregation describes a methodology for reducing the amount of
measurement data exchanged between monitoring devices (IPFIX
exporters) and analyzers (IPFIX collectors). Using aggregation
techniques, measurement information of multiple similar flows is
aggregated into one compound meta-flow record. Subsets of flows
eligible for aggregation, as well as the degree of similarity, can be
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customized using aggregation rules.
To ensure efficient communication of both aggregated flows and the
aggregation rules used, the IPFIX Protocol and IPFIX Information
Model are slightly extended to allow for two new abstract data types
and a new type of template set.
Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . 3
2. Terminology . . . . . . . . . . . . . . . . . . . . . . . . . 3
3. Architecture . . . . . . . . . . . . . . . . . . . . . . . . . 4
4. Methodology . . . . . . . . . . . . . . . . . . . . . . . . . 5
4.1 Aggregation Rules . . . . . . . . . . . . . . . . . . . . 5
4.2 Field Modifiers . . . . . . . . . . . . . . . . . . . . . 6
4.3 Patterns and Common Properties . . . . . . . . . . . . . . 7
4.4 Rule Semantics . . . . . . . . . . . . . . . . . . . . . . 7
4.5 Example . . . . . . . . . . . . . . . . . . . . . . . . . 8
5. IPFIX Extensions . . . . . . . . . . . . . . . . . . . . . . . 8
5.1 ipv4Network . . . . . . . . . . . . . . . . . . . . . . . 9
5.2 portRanges . . . . . . . . . . . . . . . . . . . . . . . . 9
5.3 Data Template . . . . . . . . . . . . . . . . . . . . . . 10
5.4 Example . . . . . . . . . . . . . . . . . . . . . . . . . 14
6. Application Examples . . . . . . . . . . . . . . . . . . . . . 16
6.1 Charging . . . . . . . . . . . . . . . . . . . . . . . . . 16
6.2 Intrusion Detection . . . . . . . . . . . . . . . . . . . 16
7. Security considerations . . . . . . . . . . . . . . . . . . . 17
8. References . . . . . . . . . . . . . . . . . . . . . . . . . . 17
8.1 Normative References . . . . . . . . . . . . . . . . . . . 17
8.2 Informative References . . . . . . . . . . . . . . . . . . 17
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . 18
Intellectual Property and Copyright Statements . . . . . . . . 19
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1. Introduction
Flow measurement in high-speed large-scale networks easily produces a
huge amount of data that can not be handled by a single IPFIX
collector or analyzer. Also, many applications processing flow
measurement data do not require detailed flow-level information but
only information about flow aggregates, where the quality and level
of flow aggregation is very application-specific. This document
presents a flexible flow aggregation scheme that helps both, reducing
the number and size of exported flow records and adapting the
transmitted measurement information to the requirements of the
application. These goals are achieved by discarding unneeded
measurement information and merging multiple individual flows into a
smaller number of compound meta-flows before the remaining
measurement data is exported to the analyzer. The following sections
show how to design and implement IPFIX aggregators and introduce
appropriate extensions to the IPFIX protocol.
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 [RFC2119].
2. Terminology
Apart from the basic terms as defined in [RFC3917], [I-D.ietf-ipfix-
protocol], and [I-D.ietf-ipfix-architecture], the following terms are
used within this document:
Meta-flow:
A meta-flow is an aggregate of individual flows.
Meta-flow record:
A meta-flow record contains the measurement data of a meta-flow.
It MAY contain the total count of all packets that belong to the
same meta-flow and were observed within a given time interval.
Flow properties that were discarded during flow aggregation are no
longer contained in the meta-flow record.
Aggregation rule:
An aggregation rule defines the properties of a meta-flow and the
content of the corresponding meta-flow record. Optionally, a set
of common properties MAY be specified in order to restrict the
applicability of the rule to those flows that show certain
patterns.
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Data Template:
A Data Template, as proposed in Section 5.3, SHOULD be used to
define the structure of the meta-flow record and to inform the
analyzer about the applied aggregation rule and the common
properties.
3. Architecture
Aggregation of measurement data may take place at two possible
stages:
o An internal aggregator, as depicted in Figure 1, is implemented as
a process running in an IPFIX enabled device. It aggregates flow
data generated by multiple metering processes and exports them as
meta-flow records. In practical implementations, metering and
aggregation MAY be performed in a single step in order to reduce
the number of retained state information.
+------------------------------------------+ +--------------+
| IPFIX-enabled device .---. .---. | | |
| .--------------------. | A | | | | .-->| Analyzer |
| | Metering Process 1 |-. | g | | E | | | | |
| `--------------------' | | g | | x | | | +--------------+
| | | r | | p |---'
| . '-->| e | | o | |
| . | g |-->| r | |
| . .-->| a | | t |---.
| | | t | | e | | | +--------------+
| .--------------------. | | o | | r | | | | |
| | Metering Process N |-' | r | | | | '-->| Concentrator |
| `--------------------' `---' `---' | | |
+------------------------------------------+ +--------------+
Figure 1: Internal Aggregation
o An external aggregator, called concentrator in IPFIX terminology,
may be used where the deployed monitoring devices cannot be
modified to incorporate an internal aggregator. Furthermore,
concentrators enable cascaded, multi-level aggregation of flow
information. As shown in Figure 2, a concentrator receives flow
records from monitoring devices and/or lower-level concentrators
and exports the aggregated meta-flow information to higher-level
concentrators and/or analyzers.
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+--------------+ +-----------------------+ +--------------+
| | | Concentrator | | |
| Concentrator |-. | .---. .---. .---. | .-->| Analyzer |
| | | | | C | | A | | | | | | |
+--------------+ | | | o | | g | | E | | | +--------------+
'--->| l | | g | | x |---'
| | l | | r | | p | |
| | e |-->| e |-->| o | |
| | c | | g | | r | |
.--->| t | | a | | t |---.
+--------------+ | | | o | | t | | e | | | +--------------+
| | | | | r | | o | | r | | | | |
| IPFIX device |-' | | | | r | | | | '-->| Concentrator |
| | | `---' `---' `---' | | |
+--------------+ +-----------------------+ +--------------+
Figure 2: External Aggregation
4. Methodology
4.1 Aggregation Rules
Regarding the configuration of the aggregator, a rule-based approach
is proposed. A list of user-defined aggregation rules is supplied to
the aggregator. An aggregation rule consists of multiple aggregation
instructions, one for each IPFIX field that is to be considered. An
aggregation instruction comprises the following elements:
o The IPFIX field the aggregation instruction refers to (e.g.
destinationIPv4Address). Only flows that contain the field
mentioned will be considered for aggregation in the meta-flow.
o One of the field modifiers "discard", "keep", "mask", or
"aggregate" that specifies how this field is treated by the
aggregator and whether it is included in the meta-flow record or
not.
o An OPTIONAL pattern for this field that restricts the aggregation
to those flows that match the given value(s) (e.g. 10.10.0.0/16).
Only flows that match all patterns of the rule will be aggregated
in the meta-flow.
With this definition of aggregation instructions each rule
unambiguously defines the content of the meta-flow record as well as
the template to export the meta-flow information. If a field is
present in the meta-flow record and how it is encoded depends on the
field modifier. This behavior is explained in Section 4.2. Fields
that do not appear in any of the aggregation instructions are not
part of the meta-flow record. The usage of patterns in order to
define common properties is explained in Section 4.3.
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4.2 Field Modifiers
The following field modifiers are applicable to fields that are part
of a flow record's Flow Key as defined in [I-D.ietf-ipfix-
architecture]:
discard:
The field is not included in the meta-flow records, i.e. meta-
flows are not distinguishable with respect to this field.
Incoming flow records with different values for this IPFIX field
are merged.
keep:
The field is included in the meta-flow record, i.e. meta-flows are
distinguishable with respect to this field. Incoming flow records
with different values for this field are not merged, but
contribute to different meta-flows instead.
mask/n (applicable to IP addresses only):
The field is included in the meta-flow record, but the number of
significant bits reduced to n bits. Incoming flow records with IP
addresses belonging to the same subnet are merged, so meta-flows
are distinguishable with respect to resulting subnet addresses
only. In accordance with the IPFIX Information Model, the
resulting subnet address MAY be encoded with a IP prefix field and
a IP mask field. It SHOULD, however, be encoded with a single
field of the new abstract data type "ipv4Network" as proposed in
Section 5.1.
If an aggregation instruction refers to a field that is not part of
the Flow Key (e.g. a time stamp or a count) the only possible field
modifier is:
aggregate:
The field is included in the meta-flow record. The value for this
field is derived from the corresponding values of the original
flows by applying an aggregation function. The type of
aggregation function to be applied depends on the field type. For
example, the meta-flow's start timestamp is set to the minimum of
the original start timestamps, packet and byte counts of
aggregated flows are summed up. Table 1 gives an overview of
common field types and their associated aggregation function.
Refer to the IPFIX Information Model [I-D.ietf-ipfix-info] for a
description of the mentioned fields.
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+-----------------------+----------------------+
| Field | Aggregation Function |
+-----------------------+----------------------+
| minimumPacketLength | minimum |
| minimumTtl | minimum |
| flowStartSeconds | minimum |
| flowStartMilliSeconds | minimum |
| maximumPacketLength | maximum |
| maximumTtl | maximum |
| flowEndSeconds | maximum |
| flowEndMilliSeconds | maximum |
| ipv6OptionHeaders | binary OR |
| tcpControlBits | binary OR |
| octetDeltaCount | sum |
| packetDeltaCount | sum |
+-----------------------+----------------------+
Table 1: Treatment of Fields Carrying Metering Information
Because the export of a meta-flow record requires an appropriate
template, a one-to-one relationship between rules and templates can
be established.
4.3 Patterns and Common Properties
The applicability of an aggregation rule MAY be restricted to flows
whose Flow Keys match certain patterns. Thus, patterns act as
filters that enable the selection of flows and meta-flows that are
exported to the analyzer. For example, the pattern "80" can be
applied to the Flow Key sourceTransportPort in order to export only
(meta-)flows originated by an HTTP server. Patterns MUST NOT be used
in combination with fields that are not part of the Flow Key, such as
the field types shown in Table 1.
The defined patterns constitute common properties of the aggregated
flows. Furthermore, the common properties are the same for all meta-
flows resulting from the corresponding aggregation rule. Common
properties MAY be exported as regular IPFIX fields. However, in
order to reduce redundancy and to make patterns distinguishable from
other fields, they SHOULD be transmitted as fixed-value fields using
the Data Template presented in Section 5.3. Additionally, encoding
common properties as fixed-value fields make the applied patterns
visible to the analyzer.
4.4 Rule Semantics
By default, incoming flow records are checked against all aggregation
rules. If a rule matches, i.e. if the flow record comprises all
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required fields and matches all given patterns, the field modifiers
are applied and the corresponding meta-flow record is generated or
updated. Therefore, incoming flow records that match multiple rules
contribute to multiple meta-flows.
In some cases, it is preferred that an incoming flow record that
matched a certain rule is not checked against other rules in order to
avoid that this flow contributes to multiple meta-flows. Therefore,
it is possible to indicate a preceding rule for each aggregation
rule. If a preceding rule is given, the aggregator tries to
aggregate an incoming flow according to the preceding rule. Only if
the preceding rule is not applicable, e.g. because the incoming flow
does not match the given pattern, the current rule is applied. Using
the preceding rule relationship, rules can be organized in rule
chains and rule trees where only the first matching rule is applied
in every chain or branch. Consequently, each flow record is counted
at most once per chain or branch. Rules that do not define a
preceding rule are used to check all incoming flow records and may
constitute the beginning of a rule chain or the root of a rule tree.
The Preceding Rule field in the header of the Data Template (see
Section 5.3) is used to identify the preceding rule by its Template
ID. If this ID is set to 0, there is no preceding rule and the rule
is checked against all incoming records.
4.5 Example
Here is an example rule with four aggregation instructions:
1. Aggregate
* discard sourceTransportPort in 80
* keep sourceIPv4Address
* mask/24 destinationIPv4Address in 10.10.0.0/16
* aggregate packetDeltaCount
This rule aggregates all flows to a destination address in the subnet
10.10.0.0/16 with source port equal to 80. Destination addresses are
merged according to subnets in 10.10.x.0/24. The resulting meta-flow
records comprise the source address, the destination subnet address,
and the packet counter.
5. IPFIX Extensions
After having a rule's field modifiers applied, all flow records that
matched a rule comprise the same fields, so for each rule exactly one
template can be used. In order to efficiently transmit aggregated
flows, three extensions to IPFIX are proposed:
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o New abstract data type "ipv4Network"
o New abstract data type "portRanges"
o New "Data Template" set
5.1 ipv4Network
Currently, the transport of IP network information as specified by
IPFIX is done using separate fields for the network address and the
corresponding mask. We propose a new abstract data type ipv4Network
that represents the common notation of IP networks: address/mask.
The new abstract data type is built of an unsigned32 for the IPv4
address and (OPTIONAL) an additional octet specifying the prefix
length. The encoding of the IPv4 address corresponds to the
definition of the ipv4Address in the IPFIX Information Model.
Although using an ipv4Network field instead of two separate fields
for prefix and mask will not reduce the length of resulting flow
records, it eases the work of the aggregator: With ipv4Network, the
comparison of subnet addresses requires only one field lookup per
record instead of two. Furthermore, using the abstract data type
ipv4Network reduces the template size by one field equalling four
octets. Applications such as IPFIX Aggregation benefit from
ipv4Network if network addresses are frequently exported.
5.2 portRanges
For some applications it might be useful to restrict the
applicability of an aggregation rule to flows with source or
destination port being of a specific set of port numbers. In an
aggregation rule, such a set of port numbers can be specified as a
pattern. However, the current IPFIX Information Model does not
define any data type that allows transmitting a set of port numbers,
which is necessary in order to export the pattern as a common
property of the resulting meta-flows. Therefore, the new abstract
data type portRanges for a list of port ranges is defined in this
section.
portRanges is a finite length string of unsigned32 values, each
consisting of an unsigned16 for the first port number followed by an
unsigned16 for the last port number of the port range. portRanges MAY
be used as a variable-length data type as defined in [I-D.ietf-ipfix-
protocol].
Data types basing on portRanges MAY also be cast down to unsigned16
to represent a single Port. Hence, the transportSourcePort and
transportDestinationPort data types, currently based on the
unsigned16 abstract data type, MAY be replaced portRanges-based data
types.
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Table 2 shows some encoding examples with portRanges.
+---------------+--------+---------------------------------+
| Ports | Length | Hexadecimal Representation |
+---------------+--------+---------------------------------+
| 80 | 2 | 0050 |
| 1:7 | 4 | 0001 0007 |
| 80, 443 | 8 | 0050 0050 01BB 01BB |
| 1:7, 256:1024 | 8 | 0001 0007 0100 0400 |
| 20, 80, 443 | 12 | 0014 0014 0050 0050 01BB 01BB |
| 1:7, 80, 443 | 12 | 0001 0007 0050 0050 01BB 01BB |
+---------------+--------+---------------------------------+
Table 2: PortRanges Examples
5.3 Data Template
Section Section 4.3 described how patterns are used to restrict the
applicability of an aggregation rule and define common properties of
the resulting meta-flows. In order to avoid the overhead of the
repeated transmission of these common properties in all meta-flow
records resulting from a given rule, the new template type Data
Template is introduced. This template type allows the exporter to
declare common properties to the analyzer. Additionally, each Data
Template Record includes a Preceding Rule field that is used to
inform the analyzer about the semantics of the aggregation rule sets.
The basic format of a Data Template Set is shown in Figure 3. It is
the same as for a Template Set, except that the Set ID is 4. The
format of individual Data Template Records, however, differs from
that of the standard Template and is shown in Figure 4.
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0 1 2 3
0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1
+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
| Set ID = 4 | Length |
+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
| |
| Data Template Record 1 |
| |
+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
| |
| ... |
| |
+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
| |
| Data Template Record N |
| |
+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
| Padding (opt) |
+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
Figure 3: Data Template Set Format
The Data Template Set field definitions are as follows:
Set ID
Type of this template set. A Set ID value of 4 is proposed for
the Data Template Set.
Length
Total length of this set in bytes.
Padding
OPTIONAL padding to fill the set to a word boundary. It MUST
consist of null-bytes and be at most seven bytes in length
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0 1 2 3
0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1
+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
| Template ID | Field Count |
+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
| Data Count | Preceding Rule |
+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
| |
| Field 1 Specifier |
| |
+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
| |
| ... |
| |
+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
| |
| Field N Specifier |
| |
+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
| |
| Data 1 Specifier |
| |
+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
| |
| ... |
| |
+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
| |
| Data M Specifier |
| |
+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
| |
| Data 1 Value |
| |
+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
| |
| ... |
| |
+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
| |
| Data M Value |
| |
+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
Figure 4: Data Template Record Format
The Data Template Record field definitions are as follows:
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Template ID
Template ID of this Data Template Record. This value is greater
than 255.
Field Count
Number of regular fields that will be sent in subsequent Data
Records using this Template.
Data Count
Number of fixed-value fields that will be sent in this Template.
Preceding Rule
Template ID of the preceding rule that is checked before, or 0 if
all incoming records are to be checked against this rule. When a
Data Template refers to a preceding rule, the Exporter SHOULD make
sure that the referred Template is also exported in order to
ensure that the Collector is able to reconstruct the rule order.
Refer to Section 4.4 for a description of organizing rules in
chains or trees.
Field N Specifier
Information Element identifier, Field length and an Enterprise
Number (if needed) of field N. Refer to [I-D.ietf-ipfix-protocol]
for more information on Field Specifiers
Data M Specifier
Same as "Field N Specifier", but used for common properties of all
Data Records of this Template. Together with Data M Value, a
similar encoding like TLV (type-length-value) is achieved.
Data M Value
Bit representation of a common property as would be transmitted in
a Data Record.
Table 3 illustrates the relationship between field modifiers and
common properties (defined as patterns) on the one hand, and the
resulting regular and fixed-value fields in the Data Template on the
other hand. It can be seen that the analyzer is able to deduce all
instructions of the aggregation rule considering the structure of the
Data Template, except the combination "discard without pattern" that
does not result in any field.
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+----------------+----------------+----------------+----------------+
| field modifier | pattern | field in | fixed-value |
| | | meta-flow | field in Data |
| | | record | Template |
+----------------+----------------+----------------+----------------+
| discard | no | N/A | N/A |
| discard | yes | N/A | yes, contains |
| | | | pattern |
| keep | no | yes | N/A |
| keep | yes | yes, if | yes, contains |
| | | pattern | pattern |
| | | specifies a | |
| | | range of | |
| | | values | |
| mask | no | yes, IP | N/A |
| | | network | |
| | | address | |
| mask | yes | yes, IP | yes, contains |
| | | network | pattern |
| | | address | |
+----------------+----------------+----------------+----------------+
Table 3: Relation between field modifiers, meta-flow records, and
Data Templates
5.4 Example
In this example we assume the concentrator was given the following
aggregation rule:
1. Aggregate
* discard sourceIPv4Address in 10.0.0.0/23
* keep destinatonTransportPort
* aggregate packetDeltaCount
We further assume the concentrator receives the following flow
records:
+------------+------------+-------------+-------------+-------------+
| Source IP | Source | Destination | Destination | Packets |
| | Port | IP | Port | |
+------------+------------+-------------+-------------+-------------+
| 10.0.0.1 | 64235 | 10.0.0.10 | 80 | 10 |
| 10.0.1.2 | 64236 | 10.0.0.11 | 110 | 10 |
| 10.0.0.3 | 64237 | 10.0.0.12 | 80 | 10 |
| 10.0.2.4 | 64238 | 10.0.0.13 | 80 | 10 |
| 10.0.2.5 | 64239 | 10.0.0.14 | 80 | 10 |
+------------+------------+-------------+-------------+-------------+
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Table 4: Incoming Flows
Based on the aggregation rule stated above the concentrator would now
first send a Data Template Set with the Data Template Record
corresponding to the given rule:
+----------------+------------------+
| Field | Value |
+----------------+------------------+
| Template ID | 10001 |
| Field Count | 2 |
| Data Count | 2 |
| Preceding Rule | 0 |
| Field 1 Type | Destination Port |
| Field 2 Type | Packets |
| Data 1 Type | Source IP Prefix |
| Data 2 Type | Source IP Mask |
| Data 1 Value | 10.0.0.0 |
| Data 2 Value | 23 |
+----------------+------------------+
Table 5: Data Template used
In case that the abstract data type ipv4Network was used for a new
data type Source IP Network, it would look like this:
+----------------+-------------------+
| Field | Value |
+----------------+-------------------+
| Template ID | 10001 |
| Field Count | 2 |
| Data Count | 2 |
| Preceding Rule | 0 |
| Field 1 Type | Destination Port |
| Field 2 Type | Packets |
| Data 1 Type | Source IP Network |
| Data 1 Value | 10.0.0.0/23 |
+----------------+-------------------+
Table 6: Data Template used
Secondly, a Data Set of this Data Template is exported containing the
meta-flows resulting from the given rule. Note that the flows'
common property, a source IP address in 10.0.0.0/23, was already
transmitted in the template. The exported meta-flow records contain
the aggregated packet counts and the destination port, which is the
only discriminating Flow Key property.
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+------------------+---------+
| Destination Port | Packets |
+------------------+---------+
| 80 | 20 |
| 110 | 10 |
+------------------+---------+
Table 7: Aggregated Flows
6. Application Examples
6.1 Charging
Charging applications require separate flow accounting for individual
end systems. However, detailed information about all individual
flows sent or received by the end system is not required. The
required level of flow aggregation can be achieved with an
aggregation rules that discards all Flow Key properties except the IP
address of the involved end systems.
The example ruleset can be used for charging end systems in the
subnet 10.10.0.0/16:
1. Aggregate
* keep destinationIPv4Address in 10.10.0.0/16
* aggregate packetDeltaCount
2. Aggregate
* keep sourceIPv4Address in 10.10.0.0/16
* aggregate packetDeltaCount
Meta-flow records resulting from the first rule contain packet counts
of the inbound traffic separated by host IP addresses. The second
rule produces the corresponding records for the outbound traffic.
Protocol and port information is omitted.
6.2 Intrusion Detection
If flow accounting is employed for intrusion detection, e.g. in order
to detect denial-of-service attacks, information about the transport
layer protocol and attacked service, i.e. the destination port, is
mostly required. On the other hand, the analysis is typically based
on flow aggregates exchanged between subnets since processing
individual flows would require to much processing power. Detailed
information about the flows between individual end systems is only
required if an already detected attack should be analyzed in more
detail.
An example ruleset might consist of the following instructions:
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Internet-Draft IPFIX Aggregation December 2005
1. Aggregate
* mask/24 destinationIPv4Address in 10.10.0.0/16
* mask/24 sourceIPv4Address
* keep protocolIdentifier
* keep destinationTransportPort
* aggregate packetDeltaCount
Meta-flow records are created for all packets directed to /24 subnets
in the protected network 10.10.0.0/16. The destination port and the
protocol are preserved whereas the source port is discarded.
7. Security considerations
As all methods described in this document are merely variations on
methods already introduced in [I-D.ietf-ipfix-protocol], the same
rules regarding exchange of flow information apply.
8. References
8.1 Normative References
[RFC2119] Bradner, S., "Key words for use in RFCs to Indicate
Requirement Levels", March 1997.
8.2 Informative References
[I-D.ietf-ipfix-architecture]
Sadasivan, G., Brownlee, N., Claise, B., and J. Quittek,
"Architecture for IP Flow Information Export",
draft-ietf-ipfix-architecture-09 (work in progress),
August 2005.
[I-D.ietf-ipfix-protocol]
Claise, B., "IPFIX Protocol Specifications",
draft-ietf-ipfix-protocol-19 (work in progress),
September 2005.
[I-D.ietf-ipfix-info]
Quittek, J., Bryant, S., Claise, B., and J. Meyer,
"Information Model for IP Flow Information Export",
draft-ietf-ipfix-info-11 (work in progress),
September 2005.
[RFC3917] Quittek, J., Zseby, T., Claise, B., and S. Zander,
"Requirements for IP Flow Information Export", RFC 3917,
October 2004.
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Internet-Draft IPFIX Aggregation December 2005
Authors' Addresses
Falko Dressler
University of Erlangen
Department of Computer Science 7
Martensstr. 3
Erlangen 91058
Germany
Phone: +49 9131 85-27914
Email: dressler@informatik.uni-erlangen.de
URI: http://www7.informatik.uni-erlangen.de/
Christoph Sommer
University of Erlangen
Department of Computer Science 7
Martensstr. 3
Erlangen 91058
Germany
Email: sichsomm@stud.informatik.uni-erlangen.de
Gerhard Muenz
University of Tuebingen
Computer Networks and Internet
Auf der Morgenstelle 10C
Tuebingen 72076
Germany
Phone: +49 7071 29-70534
Email: muenz@informatik.uni-tuebingen.de
URI: http://net.informatik.uni-tuebingen.de/
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Internet-Draft IPFIX Aggregation December 2005
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