Evaluating the Utility of Single Field Anonymization Polices by the IDS Metric : Towards measuring the trade off between Utility and Security
作者： Kiran Lakkaraju , Adam J. Slagell
DOI:
关键词: Process (engineering) 、 Data set 、 Field (computer science) 、 Metric (mathematics) 、 Information sensitivity 、 Set (abstract data type) 、 Intrusion detection system 、 Data mining 、 Computer science
摘要: Anonymization is the process of removing or hiding sensitive information in logs. allows organizations to share network logs while not exposing information. However, there an inherent trade off between amount revealed log and usefulness client (the utility a log). There are many anonymization techniques, ways anonymize particular (that is, which fields how). Different policies will result with varying levels for analysis. In this paper we explore effect different on We provide empirical analysis by looking at number alerts generated Intrusion Detection System. This first work thoroughly evaluate single field data set. Our main contributions determine set that have large impact log.
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