One document matched: draft-boschi-ipfix-anon-01.txt
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IPFIX Working Group E. Boschi
Internet-Draft B. Trammell
Intended status: Experimental Hitachi Europe
Expires: January 15, 2009 July 14, 2008
IP Flow Anonymisation Support
draft-boschi-ipfix-anon-01.txt
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Abstract
This document describes anonymisation techniques for IP flow data.
It provides a categorization of common anonymisation schemes and
defines the parameters needed to describe them. It describes support
for anonymization within the IPFIX protocol, providing the basis for
the definition of information models for configuring anonymisation
techniques within an IPFIX Metering or Exporting Process, and for
reporting the technique in use to an IPFIX Collecting Process.
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.1. IPFIX Protocol Overview . . . . . . . . . . . . . . . . . 3
1.2. IPFIX Documents Overview . . . . . . . . . . . . . . . . . 3
2. Terminology . . . . . . . . . . . . . . . . . . . . . . . . . 4
3. Categorisation of Anonymisation Techniques . . . . . . . . . . 4
4. Anonymisation of IP Flow Data . . . . . . . . . . . . . . . . 5
4.1. IP Address Anonymisation . . . . . . . . . . . . . . . . . 6
4.1.1. Truncation . . . . . . . . . . . . . . . . . . . . . . 7
4.1.2. Random Permutations . . . . . . . . . . . . . . . . . 7
4.1.3. Prefix-preserving Pseudonymisation . . . . . . . . . . 7
4.2. Timestamp Anonymisation . . . . . . . . . . . . . . . . . 7
4.2.1. Precision Degradation . . . . . . . . . . . . . . . . 7
4.2.2. Enumeration . . . . . . . . . . . . . . . . . . . . . 7
4.2.3. Random Time Shifts . . . . . . . . . . . . . . . . . . 8
4.3. Counter Anonymisation . . . . . . . . . . . . . . . . . . 8
4.3.1. Precision Degradation . . . . . . . . . . . . . . . . 8
4.3.2. Binning . . . . . . . . . . . . . . . . . . . . . . . 8
4.3.3. Random Noise Addition . . . . . . . . . . . . . . . . 8
4.4. Anonymisation of Other Flow Fields . . . . . . . . . . . . 9
5. Parameters for the Description of Anonymisation Techniques . . 9
6. Anonymisation Support in IPFIX . . . . . . . . . . . . . . . . 9
7. Security Considerations . . . . . . . . . . . . . . . . . . . 9
8. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 9
9. References . . . . . . . . . . . . . . . . . . . . . . . . . . 9
9.1. Normative References . . . . . . . . . . . . . . . . . . . 9
9.2. Informative References . . . . . . . . . . . . . . . . . . 10
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . . 10
Intellectual Property and Copyright Statements . . . . . . . . . . 12
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1. Introduction
The standardisation of an IP flow information export protocol
[RFC5101] and associated representations removes a technical barrier
to the sharing of IP flow data across organizational boundaries and
with network operations, security, and research communities for a
wide variety of purposes. However, with wider dissemination comes
greater risks to the privacy of the users of networks under
measurement, and to the security of those networks. While it is not
a complete solution to the issues posed by distribution of IP flow
information, anonymisation is an important tool for the protection of
privacy within network measurement infrastructures.
This document presents a mechanism for representing anonymised data
within IPFIX and guidelines for using it. It begins with a
categorization of anonymisation techniques. It then describes
applicability of each technique to commonly anonymisable fields of IP
flow data, organized by information element data type and semantics
as in [RFC5102]; enumerates the parameters required by each of the
applicable anonymisation techniques; and provides guidelines for the
use of each of these techniques in accordance with best practices in
data protection. Finally, it specifies a mechanism for exporting
anonymised data and binding anonymisation metadata to templates using
IPFIX Options.
1.1. IPFIX Protocol Overview
In the IPFIX protocol, { type, length, value } tuples are expressed
in templates containing { type, length } pairs, specifying which {
value } fields are present in data records conforming to the
Template, giving great flexibility as to what data is transmitted.
Since Templates are sent very infrequently compared with Data
Records, this results in significant bandwidth savings. Various
different data formats may be transmitted simply by sending new
Templates specifying the { type, length } pairs for the new data
format. See [RFC5101] for more information.
The IPFIX information model [RFC5102] defines a large number of
standard Information Elements which provide the necessary { type }
information for Templates. The use of standard elements enables
interoperability among different vendors' implementations.
Additionally, non-standard enterprise-specific elements may be
defined for private use.
1.2. IPFIX Documents Overview
"Specification of the IPFIX Protocol for the Exchange of IP Traffic
Flow Information" [RFC5101] and its associated documents define the
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IPFIX Protocol, which provides network engineers and administrators
with access to IP traffic flow information.
"Architecture for IP Flow Information Export" [I-D.ietf-ipfix-arch]
defines the architecture for the export of measured IP flow
information out of an IPFIX Exporting Process to an IPFIX Collecting
Process, and the basic terminology used to describe the elements of
this architecture, per the requirements defined in "Requirements for
IP Flow Information Export" [RFC3917]. The IPFIX Protocol document
[RFC5101] then covers the details of the method for transporting
IPFIX Data Records and Templates via a congestion-aware transport
protocol from an IPFIX Exporting Process to an IPFIX Collecting
Process.
"Information Model for IP Flow Information Export" [RFC5102]
describes the Information Elements used by IPFIX, including details
on Information Element naming, numbering, and data type encoding.
Finally, "IPFIX Applicability" [I-D.ietf-ipfix-as] describes the
various applications of the IPFIX protocol and their use of
information exported via IPFIX, and relates the IPFIX architecture to
other measurement architectures and frameworks.
This document references the Protocol and Architecture documents for
terminology and extends the IPFIX Information Model to provide new
Information Elements for anonymisation metadata.
2. Terminology
Terms used in this document that are defined in the Terminology
section of the IPFIX Protocol [RFC5101] document are to be
interpreted as defined there.
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 RFC 2119 [RFC2119].
3. Categorisation of Anonymisation Techniques
Anonymisation modifies a data set in order to protect the identity of
the people or entities described by the data set from disclosure.
With respect to network traffic data, anonymisation generally
attempts to preserve some set of properties of the network traffic
useful for a given application or applications, while ensuring the
data cannot be traced back to the specific networks, hosts, or users
generating the traffic.
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Anonymisation may be broadly split into three categories:
generalisation and reversible or irreversible substitution. When
generalisation is used, identifying information is grouped in sets,
and one single value is used to identify each set element. In
effect, this causes multiple records to become indistinguishable,
thereby aggregating them together. Generalisation is an irreversible
operation, in that the information needed to identify a single record
from its "generalised value" is lost.
Substitution (or pseudonymization) maps the real space of identifiers
or values into a separate, replacement space, using some substitution
function. If the substitution function is invertible or can
otherwise be reversed, then the substitution is reversible, and a
real identifier can be recovered from a given replacement identifier.
This allows to keep different elements distinguishable from each
other: the number of different elements in the real and the
replacement space is the same.
Irreversible substitution results when a randomising or one-way
function is used to map the value space; real identifiers cannot be
recovered in an irreversible substitution. The number of different
elements in the real and replacement spaces is not necessarily the
same.
4. Anonymisation of IP Flow Data
Due to the restricted semantics of IP flow data, there are a
relatively limited set of specific anonymisation techniques available
on flow data, though each falls into the broad categories above.
Each type of field that may commonly appear in a flow record may have
its own applicable specific techniques.
While anonymisation is generally applied at the resolution of single
fields within a flow record, attacks against anonymisation use entire
flows and relationships between hosts and flows within a given data
set. Therefore, fields which may not necessarily be identifying by
themselves may be anonymised in order to increase the anonymity of
the data set as a whole.
Of all the fields in an IP flow record, only IP addresses directly
identify entities in the real world. Each IP address is associated
with an interface on a network host, and can potentially be
identified with a single user. Additionally, IP addresses are
structured identifiers; that is, partial IP address prefixes may be
used to identify networks just as full IP addresses identify hosts.
This makes anonymisation of IP addresses particularly important.
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Port numbers identify abstract entities (applications) as opposed to
real-world entities, but they can be used to classify hosts and user
behavior. Passive port fingerprinting, both of well-known and
ephemeral ports, can be used to determine the operating system
running on a host. Relative data volumes by port can also be used to
determine the host's function (workstation, web server, etc.); this
information can be used to identify hosts and users.
While not identifiers in and of themselves, timestamps and counters
can reveal the behavior of the hosts and users on a network. Any
given network activity is recognizable by a pattern of relative time
differences and data volumes in the associated sequence of flows,
even without host address information. They can therefore be used to
identify hosts and users. Timestamps and counters are also
vulnerable to traffic injection attacks, where traffic with a known
pattern is injected into a network under measurement, and this
pattern is later identified in the anonymised data set.
The simplest and most extreme form of anonymisation, which can be
applied to any field of a flow record, is black-marker anonymisation,
or complete deletion of a given field. While black-marker
anonymisation completely protects the data in the deleted fields from
the risk of disclosure, it also reduces the utility of the anonymised
data set as a whole. Techniques that retain some information while
reducing (though not eliminating) the disclosure risk will be
extensively discussed in the following sections; note that the
techniques specifically applicable to IP addresses, timestamps, and
counters will be discussed in separate sections.
4.1. IP Address Anonymisation
The following table gives an overview of the schemes for IP address
anonymization described in this document and their categorization.
+----------------------------------+----------------+---------------+
| Scheme | Action | Reversibility |
+----------------------------------+----------------+---------------+
| Truncation | Generalisation | N |
| Random Permutation | Substitution | Y/N |
| Prefix-preserving | Substitution | Y |
| Pseudonymisation | | |
+----------------------------------+----------------+---------------+
Note that random permutations might be either reversible or not,
depending on the function used.
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4.1.1. Truncation
Truncation removes "n" of the least significant bits from an IP
Address. Note that truncating 8 bits would replace an IP Address
with the corresponding class C network address.
4.1.2. Random Permutations
When random permutations are used, each IP Address is replaced with a
random permutation on the set of possible IP Addresses. The
permutation function can be implemented using hash tables.
4.1.3. Prefix-preserving Pseudonymisation
Prefix-preserving pseudonymisation preserves the structure of IP
Addresses. If two IP Addresses match on a prefix of "n" bits, their
anonymised versions will match on a prefix of "n" bits too.
4.2. Timestamp Anonymisation
[TODO: introductory text]
+-----------------------+----------------+---------------+
| Scheme | Action | Reversibility |
+-----------------------+----------------+---------------+
| Precision Degradation | Generalisation | N |
| Enumeration | Substitution | Y |
| Random Shifts | Substitution | Y |
+-----------------------+----------------+---------------+
4.2.1. Precision Degradation
Precision Degradation removes the most precise components of a
timestamp, accounting all events occurring in each given interval
(e.g. one millisecond for millisecond level degradation) as
simultaneous. This has the effect of potentially collapsing many
timestamps into one. With this technique time precision is reduced,
and sequencing may be lost, but the information at which time the
event happened is kept.
4.2.2. Enumeration
Enumeration keeps the chronological order in which events occurred
while eliminating time information. Timestamps are substituted by
equidistant timestamps (or numbers) starting from an rendomly chosen
start value.
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4.2.3. Random Time Shifts
Random Time Shifts keep the information on how far apart two events
are from each other. This is achieved by shifting all timestamps by
the same random number. Note that random time shifts also preserve
chronological order.
4.3. Counter Anonymisation
Counters (such as packet and octet volumes per flow) are subject to
fingerprinting and injection attacks against anonymisation, as
timestamps are, but relative magnitudes of activity can be useful for
certain analysis tasks. [TODO: more intro text]
+-----------------------+----------------+---------------+
| Scheme | Action | Reversibility |
+-----------------------+----------------+---------------+
| Precision Degradation | Generalisation | N |
| Binning | Generalisation | N |
| Random noise addition | Substitution | N |
+-----------------------+----------------+---------------+
4.3.1. Precision Degradation
As with precision degradation in timestamps, precision degradation of
counters removes lower-order bits of the counters, treating all the
counters in a given range as having the same value. Depending on the
precision reduction, this loses information about the relationships
between sizes of similarly-sized flows, but keeps relative magnitude
information.
4.3.2. Binning
Binning can be seen as a special case of precision degradation; the
operation is identical, except for in precision degradation the
counter ranges are uniform, and in binning they need not be. For
example, a common counter binning scheme for packet counters could be
to bin values 1-2 together, and 3-infinity together, thereby
separating potentially completely-opened TCP connections from
unopened ones. Binning schemes are generally chosen to keep
precisely the amount of information required in a counter for a given
analysis task
4.3.3. Random Noise Addition
Random noise addition adds a random amount to a counter in each flow;
this is used to keep relative magnitude information and minimize the
disruption to size relationship information while avoiding
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fingerprinting attacks against anonymization.
4.4. Anonymisation of Other Flow Fields
[TODO: as section 4.1]
5. Parameters for the Description of Anonymisation Techniques
[TODO: see corresponding section of draft-ietf-psamp-sample-tech for
the proposed structure of this section.]
6. Anonymisation Support in IPFIX
[TODO: Here we'll describe how the information specified above can be
transmitted on the wire using an option template. The idea is to
scope the option to the Template ID and for each field specify which
are anonymised, providing info on the output characteristics of the
technique, and which ones aren't.]
[EDITOR'S NOTE: Multiple anon. techniques applied on an IE at the
same time is indicated with multiple elements of the same type (in
application order as in PSAMP)]
[EDITOR'S NOTE: for blackmarking we'll recommend not to export the
information at all following the data protection law principle that
only necessary information should be exported.]
7. Security Considerations
[TODO: write this section.]
8. IANA Considerations
This document contains no actions for IANA.
9. References
9.1. Normative References
[RFC5101] Claise, B., "Specification of the IP Flow Information
Export (IPFIX) Protocol for the Exchange of IP Traffic
Flow Information", RFC 5101, January 2008.
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[RFC5102] Quittek, J., Bryant, S., Claise, B., Aitken, P., and J.
Meyer, "Information Model for IP Flow Information Export",
RFC 5102, January 2008.
9.2. Informative References
[I-D.ietf-ipfix-arch]
Sadasivan, G. and N. Brownlee, "Architecture Model for IP
Flow Information Export", draft-ietf-ipfix-arch-02 (work
in progress), October 2003.
[I-D.ietf-ipfix-as]
Zseby, T., "IPFIX Applicability", draft-ietf-ipfix-as-12
(work in progress), July 2007.
[I-D.ietf-ipfix-architecture]
Sadasivan, G., "Architecture for IP Flow Information
Export", draft-ietf-ipfix-architecture-12 (work in
progress), September 2006.
[I-D.ietf-ipfix-reducing-redundancy]
Boschi, E., "Reducing Redundancy in IP Flow Information
Export (IPFIX) and Packet Sampling (PSAMP) Reports",
draft-ietf-ipfix-reducing-redundancy-04 (work in
progress), May 2007.
[RFC3917] Quittek, J., Zseby, T., Claise, B., and S. Zander,
"Requirements for IP Flow Information Export (IPFIX)",
RFC 3917, October 2004.
[RFC2119] Bradner, S., "Key words for use in RFCs to Indicate
Requirement Levels", BCP 14, RFC 2119, March 1997.
Authors' Addresses
Elisa Boschi
Hitachi Europe
c/o ETH Zurich
Gloriastrasse 35
8092 Zurich
Switzerland
Phone: +41 44 632 70 57
Email: elisa.boschi@hitachi-eu.com
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Brian Trammell
Hitachi Europe
c/o ETH Zurich
Gloriastrasse 35
8092 Zurich
Switzerland
Phone: +41 44 632 70 13
Email: brian.trammell@hitachi-eu.com
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