Article

A method to compress and anonymize packet traces

Author:

Markus PeuhkuriAuthors Info & Claims

IMW '01: Proceedings of the 1st ACM SIGCOMM Workshop on Internet measurement

Pages 257 - 261

https://doi.org/10.1145/505202.505233

Published: 01 November 2001 Publication History

Get Access

Abstract

Data volume and privacy issues are one of problems related to large-scale packet capture. Utilizing flow nature of Internet traffic can reduce data volume. Removing sensitive information such as IP addresses enchanges privacy. Our method makes possible to have same replacement value for given IP address even if capture location or time is different.

References

[1]

V. Jacobson, "Compressing TCP/IP headers for low-speed serial links," Request for Comments RFC 1144, Internet Engineering Task Force, Feb. 1990.]]

Digital Library

Google Scholar

[2]

M. Degermark, B. Nordgren, and S. Pink, "IP Header Compression," Request for Comments RFC 2507, Internet Engineering Task Force, Feb. 1999.]]

Digital Library

Google Scholar

[3]

K.C. Claffy, H.-W. Braun, and G.C. Polyzos, "A parameterizable methodology for intemet traffic flow profiling," IEEE Journal on Selected Areas in Communications, pp. 1481 - 1494, Oct. 1995.]]

Digital Library

Google Scholar

[4]

M. Mathis, J. Mahdavi, S. Floyd, and A. Romanow, "TCP Selective Acknowledgement Options," Request for Comments RFC 2018, Internet Engineering Task Force, Oct. 1996.]]

Digital Library

Google Scholar

[5]

V. Jacobson, R. Braden, and D. Borman, "TCP Extensions for High Performance," Request for Comments RFC 1323, Internet Engineering Task Force, May 1992.]]

Digital Library

Google Scholar

[6]

J. Postel, "Transmission Control Protocol," Request for Comments RFC 793, Internet Engineering Task Force, Sept. 198 1.]]

Google Scholar

[7]

J. Postel, "Internet Protocol," Request for Comments RFC 791, Internet Engineering Task Force, Sept. 1981.]]

Google Scholar

[8]

I. Postel, "User Datagram Protocol," Request for Comments RFC 768, Internet Engineering Task Force, Aug. 1980.]]

Digital Library

Google Scholar

[9]

Bruce Schneier, Applied Cryptography Second Edition : protocols. algorithms, and source code in C, John Wiley & Sons, Inc., 1996.]]

Digital Library

Google Scholar

[10]

R. Rivest, "The MD5 Message-Digest Algorithm," Request for Comments RFC 132 1, Internet Engineering Task Force, Apr. 1992.]]

Digital Library

Google Scholar

[11]

P. Ferguson and D. Senie, "Network Ingress Filtering: Defeating Denial of Service Attacks which employ IP Source Address Spoofing," Request for Comments RFC 2827, Internet Engineering Task Force, May 2000.]]

Digital Library

Google Scholar

[12]

"The dag project," On web, http://dag.cs.waikato.ac.nz, Referred2001-06-26.]]

Google Scholar

[13]

Technical Committee, "LAN emulation over ATM version 2.0 LUNI specification," Tech. Rep. af-lane-0084.000, The ATM Forum, July 1997.]]

Google Scholar

Cited By

View all

Favale TTrevisan MDrago IMellia M(2021) α -MON: Traffic Anonymizer for Passive Monitoring IEEE Transactions on Network and Service Management10.1109/TNSM.2021.305792718:2(1233-1245)Online publication date: Jun-2021
https://doi.org/10.1109/TNSM.2021.3057927
Favale TTrevisan MDrago IMellia M(2020)α-MON: Anonymized Passive Traffic Monitoring2020 32nd International Teletraffic Congress (ITC 32)10.1109/ITC3249928.2020.00010(10-18)Online publication date: Sep-2020
https://doi.org/10.1109/ITC3249928.2020.00010
Aleroud AChen ZKarabatis G(2016)Network Trace Anonymization Using a Prefix-Preserving Condensation-Based Technique (Short paper)On the Move to Meaningful Internet Systems: OTM 2016 Conferences10.1007/978-3-319-48472-3_59(934-942)Online publication date: 18-Oct-2016
https://doi.org/10.1007/978-3-319-48472-3_59
Show More Cited By

Index Terms

A method to compress and anonymize packet traces
1. Information systems
  1. Data management systems
    1. Data structures
      1. Data layout
        Data compression
2. Networks
  1. Network types
    1. Packet-switching networks

Recommendations

An Anonymization Method Based on Tradeoff between Utility and Privacy for Data Publishing
ICMECG '12: Proceedings of the 2012 International Conference on Management of e-Commerce and e-Government

Privacy preserving is an important issue in data publishing. Many anonymization algorithms are available in meeting the privacy requirements of the privacy models such as k-anonymity, l-diversity and t-closeness. In this paper, we discuss the ...
Making Quantitative Measurements of Privacy/Analysis Tradeoffs Inherent to Packet Trace Anonymization
Financial Cryptography and Data Security

Anonymization provides a mechanism for sharing data while obscuring private/sensitive values within the shared data. However, anonymization for sharing also sets up a fundamental tradeoff --- the stronger the anonymization protection, the less ...
A Survey on Privacy Preserving Dynamic Data Publishing

Many organizations, especially small and medium business SMB enterprises require the collection and sharing of data containing personal information. The privacy of this data must be preserved before outsourcing to the commercial public. Privacy ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

IMW '01: Proceedings of the 1st ACM SIGCOMM Workshop on Internet measurement

November 2001

319 pages

ISBN:1581134355

DOI:10.1145/505202

Conference Chair:
Vern Paxson
ACIRI

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 November 2001

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Article

Conference

SIGCOMM WS'01

Sponsor:

SIGCOMM

SIGCOMM WS'01: ACM SIGCOMM Internet Measurement Workshop 2001

November 1 - 2, 2001

California, San Francisco, USA

Acceptance Rates

IMW '01 Paper Acceptance Rate 29 of 80 submissions, 36%;

Overall Acceptance Rate 29 of 80 submissions, 36%

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

34
Total Citations
View Citations
529
Total Downloads

Downloads (Last 12 months)3
Downloads (Last 6 weeks)0

Reflects downloads up to 10 Feb 2025

Other Metrics

View Author Metrics

Citations

Cited By

View all

Favale TTrevisan MDrago IMellia M(2021) α -MON: Traffic Anonymizer for Passive Monitoring IEEE Transactions on Network and Service Management10.1109/TNSM.2021.305792718:2(1233-1245)Online publication date: Jun-2021
https://doi.org/10.1109/TNSM.2021.3057927
Favale TTrevisan MDrago IMellia M(2020)α-MON: Anonymized Passive Traffic Monitoring2020 32nd International Teletraffic Congress (ITC 32)10.1109/ITC3249928.2020.00010(10-18)Online publication date: Sep-2020
https://doi.org/10.1109/ITC3249928.2020.00010
Aleroud AChen ZKarabatis G(2016)Network Trace Anonymization Using a Prefix-Preserving Condensation-Based Technique (Short paper)On the Move to Meaningful Internet Systems: OTM 2016 Conferences10.1007/978-3-319-48472-3_59(934-942)Online publication date: 18-Oct-2016
https://doi.org/10.1007/978-3-319-48472-3_59
Gad RKappes MMedina-Bulo I(2015)Monitoring traffic in computer networks with dynamic distributed remote packet capturing2015 IEEE International Conference on Communications (ICC)10.1109/ICC.2015.7249240(5759-5764)Online publication date: Jun-2015
https://doi.org/10.1109/ICC.2015.7249240
Papadopoulos PPetsas TChristou GVasiliadis G(2015)MAD: A Middleware Framework for Multi-step Attack Detection2015 4th International Workshop on Building Analysis Datasets and Gathering Experience Returns for Security (BADGERS)10.1109/BADGERS.2015.012(8-15)Online publication date: Nov-2015
https://doi.org/10.1109/BADGERS.2015.012
Antonello RFernandes SSadok DKelner JSzabó G(2015)Design and optimizations for efficient regular expression matching in DPI systemsComputer Communications10.1016/j.comcom.2014.12.01161:C(103-120)Online publication date: 1-May-2015
https://dl.acm.org/doi/10.1016/j.comcom.2014.12.011
Lin YLu CLai YEliezer Z(2014)Bug traces: identifying and downsizing packet traces with failures triggered in networking devicesIEEE Communications Magazine10.1109/MCOM.2014.680795552:4(112-119)Online publication date: Apr-2014
https://doi.org/10.1109/MCOM.2014.6807955
Aceto GBotta APescape AWestphal C(2013)Efficient Storage and Processing of High-Volume Network Monitoring DataIEEE Transactions on Network and Service Management10.1109/TNSM.2013.011713.11021510:2(162-175)Online publication date: Jun-2013
https://doi.org/10.1109/TNSM.2013.011713.110215
Farah TTrajkovic L(2013)Anonym: A tool for anonymization of the Internet traffic2013 IEEE International Conference on Cybernetics (CYBCO)10.1109/CYBConf.2013.6617434(261-266)Online publication date: Jun-2013
https://doi.org/10.1109/CYBConf.2013.6617434
Shiravi HShiravi AGhorbani A(2012)A Survey of Visualization Systems for Network SecurityIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2011.14418:8(1313-1329)Online publication date: 1-Aug-2012
https://dl.acm.org/doi/10.1109/TVCG.2011.144
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Abstract

References

Cited By

Index Terms

Recommendations

An Anonymization Method Based on Tradeoff between Utility and Privacy for Data Publishing

Making Quantitative Measurements of Privacy/Analysis Tradeoffs Inherent to Packet Trace Anonymization

A Survey on Privacy Preserving Dynamic Data Publishing

Comments

Information

Published In

Sponsors

Publisher

Publication History

Permissions

Check for updates

Author Tags

Qualifiers

Conference

Acceptance Rates

Contributors

Other Metrics

Bibliometrics

Article Metrics

Other Metrics

Citations

Cited By

Login options

Full Access

View options

PDF

eReader

Share

Share this Publication link

Share on social media

Affiliations