A method to compress and anonymize packet traces
@inproceedings{Peuhkuri2001AMT, title={A method to compress and anonymize packet traces}, author={Markus Peuhkuri}, booktitle={IMW '01}, year={2001} }
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.
69 Citations
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A suite of three algorithms employing packet injection and frequency analysis, which can compromise individual addresses protected with prefix-preserving anonymization in multilinear time are presented and an algorithm that strengthens some hash-based anonymization methods is introduced.
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- Computer ScienceICICS
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- 2013
An anonymization tool that executes multilevel anonymization and displays analysis results is proposed and implemented and architecture and features of the tool are described and discussed and analysis of un-anonymized and anonymized datasets are discussed.
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- Computer Science2020 32nd International Teletraffic Congress (ITC 32)
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Packet measurements are essential for several applications, such as cyber-security, accounting and troubleshooting. They, however, threaten privacy by exposing sensitive information. Anonymization…
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The impact of z-anonymity on traffic measurements is quantified, finding that it introduces minimal error when it comes to finding heavy-hitter services.
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- Computer Science2006 IEEE/IFIP Network Operations and Management Symposium NOMS 2006
- 2006
SANTT employs a novel prefix-preserving anonymization method to sanitize privacy information in packets and takes advantage of specific high-speed traffic capturing hardware to share valuable network traffic traces safely and widely.
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It is proposed that optimal network data sharing needs to have different levels of anonymization tailored to the participating organizations in order to tradeoff the risks of potential loss or disclosure of sensitive information.
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- Computer Science
- 2012
This paper intends to compare the Crypto-PAn, Lucent’s extensions to Crypto- PAn, Anontool, and FLAIM, and compare the cumulative distribution function of the anonymized data.
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