Towards the evaluation of time series protection methods

DOI10.1016/j.ins.2009.01.024zbMath1179.68056OpenAlexW2052367326WikidataQ57608883 ScholiaQ57608883MaRDI QIDQ833741

Jordi Nin, Vincenç Torra

Publication date: 14 August 2009

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ins.2009.01.024

zbMATH Keywords

statistical disclosure controlinformation loss measuresprivacy in statistical databasestime series privacy

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Database theory (68P15) Data encryption (aspects in computer science) (68P25)

Related Items

Swarm-based translation-invariant morphological prediction method for financial time series forecasting, Shape-Sphere: a metric space for analysing time series by their shape, Safe MBR-transformation in similar sequence matching

Uses Software

• itsmr

Cites Work

• Privacy-preserving algorithms for distributed mining of frequent itemsets
• Time series forecasting with a nonlinear model and the scatter search meta-heuristic
• Two methods for privacy preserving data mining with malicious participants
• Clustering of time series data -- a survey
• Achieving anonymity via clustering
• Extending Microaggregation Procedures for Time Series Protection
• Introduction to Time Series and Forecasting
• EXACT AND APPROXIMATE METHODS FOR DATA DIRECTED MICROAGGREGATION IN ONE OR MORE DIMENSIONS
• k-ANONYMITY: A MODEL FOR PROTECTING PRIVACY
• ACHIEVING k-ANONYMITY PRIVACY PROTECTION USING GENERALIZATION AND SUPPRESSION
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