Anonymization of System Logs for Preserving Privacy and Reducing Storage
S. Ghiasvand, and F. Ciorba. Proceedings of the 2018 Future of Information and Communications Conference (FICC), 1, page 440--447. Singapore, Springer, (April 2018)
DOI: 10.1007/978-3-030-03405-4_11
Abstract
System logs constitute valuable information for analysis and diagnosis of systems behavior. The analysis is highly time-consuming for large log volumes. For many parallel computing centers, outsourcing the analysis of system logs (syslogs) to third parties is the only option. Therefore, a general analysis and diagnosis solution is needed. Such a solution is possible only through the syslog analysis from multiple computing systems. The data within syslogs can be sensitive, thus obstructing the sharing of syslogs across institutions, third party entities, or in the public domain. This work proposes a new method for the anonymization of syslogs that employs de-identification and encoding to provide fully shareable system logs. In addition to eliminating the sensitive data within the test logs, the proposed anonymization method provides 25\% performance improvement in post-processing of the anonymized syslogs, and more than 80\% reduction in their required storage space.
Proceedings of the 2018 Future of Information and Communications Conference (FICC)
year
2018
month
apr
pages
440--447
publisher
Springer
volume
1
isbn
978-1-5386-2056-4 978-3-030-03404-7
language
en
file
Ghiasvand and Ciorba - 2018 - Anonymization of System Logs for Preserving Privac.pdf:D\:\\Documents\\Zotero\\storage\Ł65YLSF4\\Ghiasvand and Ciorba - 2018 - Anonymization of System Logs for Preserving Privac.pdf:application/pdf
%0 Conference Paper
%1 ghiasvand2018anonymization
%A Ghiasvand, Siavash
%A Ciorba, Florina M
%B Proceedings of the 2018 Future of Information and Communications Conference (FICC)
%C Singapore
%D 2018
%I Springer
%K myOwn
%P 440--447
%R 10.1007/978-3-030-03405-4_11
%T Anonymization of System Logs for Preserving Privacy and Reducing Storage
%V 1
%X System logs constitute valuable information for analysis and diagnosis of systems behavior. The analysis is highly time-consuming for large log volumes. For many parallel computing centers, outsourcing the analysis of system logs (syslogs) to third parties is the only option. Therefore, a general analysis and diagnosis solution is needed. Such a solution is possible only through the syslog analysis from multiple computing systems. The data within syslogs can be sensitive, thus obstructing the sharing of syslogs across institutions, third party entities, or in the public domain. This work proposes a new method for the anonymization of syslogs that employs de-identification and encoding to provide fully shareable system logs. In addition to eliminating the sensitive data within the test logs, the proposed anonymization method provides 25\% performance improvement in post-processing of the anonymized syslogs, and more than 80\% reduction in their required storage space.
%@ 978-1-5386-2056-4 978-3-030-03404-7
@inproceedings{ghiasvand2018anonymization,
abstract = {System logs constitute valuable information for analysis and diagnosis of systems behavior. The analysis is highly time-consuming for large log volumes. For many parallel computing centers, outsourcing the analysis of system logs (syslogs) to third parties is the only option. Therefore, a general analysis and diagnosis solution is needed. Such a solution is possible only through the syslog analysis from multiple computing systems. The data within syslogs can be sensitive, thus obstructing the sharing of syslogs across institutions, third party entities, or in the public domain. This work proposes a new method for the anonymization of syslogs that employs de-identification and encoding to provide fully shareable system logs. In addition to eliminating the sensitive data within the test logs, the proposed anonymization method provides 25\% performance improvement in post-processing of the anonymized syslogs, and more than 80\% reduction in their required storage space.},
added-at = {2024-12-10T16:17:47.000+0100},
address = {Singapore},
author = {Ghiasvand, Siavash and Ciorba, Florina M},
biburl = {https://puma.scadsai.uni-leipzig.de/bibtex/23b359bc061a2426b6d04f26795644a19/ghiasvan},
booktitle = {Proceedings of the 2018 {Future} of {Information} and {Communications} {Conference} ({FICC})},
doi = {10.1007/978-3-030-03405-4_11},
file = {Ghiasvand and Ciorba - 2018 - Anonymization of System Logs for Preserving Privac.pdf:D\:\\Documents\\Zotero\\storage\\L65YLSF4\\Ghiasvand and Ciorba - 2018 - Anonymization of System Logs for Preserving Privac.pdf:application/pdf},
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intrahash = {3b359bc061a2426b6d04f26795644a19},
isbn = {978-1-5386-2056-4 978-3-030-03404-7},
keywords = {myOwn},
language = {en},
month = apr,
pages = {440--447},
publisher = {Springer},
timestamp = {2024-12-10T16:27:52.000+0100},
title = {Anonymization of {System} {Logs} for {Preserving} {Privacy} and {Reducing} {Storage}},
volume = 1,
year = 2018
}