Logo des Repositoriums
 

Pseudonymizing Log Entries with time-selective Disclosure

Kurzanzeige
dc.contributor.authorSonntag, Michael
dc.contributor.editorCzarnecki, Christian
dc.contributor.editorBrockmann, Carsten
dc.contributor.editorSultanow, Eldar
dc.contributor.editorKoschmider, Agnes
dc.contributor.editorSelzer, Annika
dc.date.accessioned2018-10-10T10:43:36Z
dc.date.available2018-10-10T10:43:36Z
dc.date.issued2018
dc.description.abstractCentralized logging of entries containing personally-identifiable data, like IP addresses, is common. However, this chances that persons other than the operator of the individual server might obtain access to these logs and then disclose or use them. Additionally, the GDPR recommends as a security measure pseudonymization, i.e. splitting the information into two parts. This article describes a method to pseudonymize personal information in elements stored in a time series. After a predetermined time, the information can be automatically anonymized without requiring any changes in the stored entries themselves. Additionally, some statistical analyses remain possible, as the same values are encoded with the same pseudonym. It is also possible to disclose an arbitrary time period from within the log file: everything after the start time and before the end time can be de-pseudonymized, but the rest of the data remains anon-/pseudonymous.en
dc.identifier.isbn978-3-88579-679-4
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/17211
dc.language.isoen
dc.publisherKöllen Druck+Verlag GmbH
dc.relation.ispartofWorkshops der INFORMATIK 2018 - Architekturen, Prozesse, Sicherheit und Nachhaltigkeit
dc.relation.ispartofseriesLecture Notes in Informatics
dc.subjectPseudonymization
dc.subjectanonymization
dc.subjectlog files
dc.subjectselective disclosure
dc.titlePseudonymizing Log Entries with time-selective Disclosureen
dc.typeText/Conference Paper
gi.citation.endPage127
gi.citation.publisherPlaceBonn
gi.citation.startPage119
gi.conference.date26.-27.09.2018
gi.conference.locationBerlin
gi.conference.sessiontitleSecurity & Privacy at Large

Dateien

Originalbündel
1 - 1 von 1
Vorschaubild
Name:
3032414_GI_P_285_11.pdf
Größe:
173.59 KB
Format:
Adobe Portable Document Format
Herunterladen

Sammlungen

P285 - INFORMATIK 2018 - Architekturen, Prozesse, Sicherheit und Nachhaltigkeit - Workshopband