Uncertainty principles and signal recovery
SIAM Journal on Applied Mathematics
Secure statistical databases with random sample queries
ACM Transactions on Database Systems (TODS)
Privacy-preserving data mining
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
On the design and quantification of privacy preserving data mining algorithms
PODS '01 Proceedings of the twentieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Wavelet synopses with error guarantees
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Surfing Wavelets on Streams: One-Pass Summaries for Approximate Aggregate Queries
Proceedings of the 27th International Conference on Very Large Data Bases
A survey on wavelet applications in data mining
ACM SIGKDD Explorations Newsletter
Limiting privacy breaches in privacy preserving data mining
Proceedings of the twenty-second ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
k-anonymity: a model for protecting privacy
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Privacy preserving association rule mining in vertically partitioned data
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
On the Privacy Preserving Properties of Random Data Perturbation Techniques
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Efficient elastic burst detection in data streams
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Using randomized response techniques for privacy-preserving data mining
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Privacy and Ownership Preserving of Outsourced Medical Data
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Practical privacy: the SuLQ framework
Proceedings of the twenty-fourth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Deriving private information from randomized data
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
One-pass wavelet synopses for maximum-error metrics
VLDB '05 Proceedings of the 31st international conference on Very large data bases
On k-anonymity and the curse of dimensionality
VLDB '05 Proceedings of the 31st international conference on Very large data bases
IEEE Transactions on Knowledge and Data Engineering
Privacy Preserving Data Classification with Rotation Perturbation
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
Structural Periodic Measures for Time-Series Data
Data Mining and Knowledge Discovery
Rights Protection for Discrete Numeric Streams
IEEE Transactions on Knowledge and Data Engineering
\ell -Diversity: Privacy Beyond \kappa -Anonymity
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Injecting utility into anonymized datasets
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Personalized privacy preservation
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
StatStream: statistical monitoring of thousands of data streams in real time
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Adaptive, hands-off stream mining
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Calibrating noise to sensitivity in private data analysis
TCC'06 Proceedings of the Third conference on Theory of Cryptography
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
De-noising by soft-thresholding
IEEE Transactions on Information Theory
PoolView: stream privacy for grassroots participatory sensing
Proceedings of the 6th ACM conference on Embedded network sensor systems
Probabilistic Inverse Ranking Queries over Uncertain Data
DASFAA '09 Proceedings of the 14th International Conference on Database Systems for Advanced Applications
Preserving Privacy in Time Series Data Classification by Discretization
MLDM '09 Proceedings of the 6th International Conference on Machine Learning and Data Mining in Pattern Recognition
Privacy-Preserving Data Publishing
Foundations and Trends in Databases
Privacy-preserving data publishing: A survey of recent developments
ACM Computing Surveys (CSUR)
Differentially private aggregation of distributed time-series with transformation and encryption
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Enabling search services on outsourced private spatial data
The VLDB Journal — The International Journal on Very Large Data Bases
Meaningful selection of temporal resolution for dynamic networks
Proceedings of the Eighth Workshop on Mining and Learning with Graphs
Publishing time-series data under preservation of privacy and distance orders
DEXA'10 Proceedings of the 21st international conference on Database and expert systems applications: Part II
Finding the least influenced set in uncertain databases
Information Systems
Probabilistic inverse ranking queries in uncertain databases
The VLDB Journal — The International Journal on Very Large Data Bases
Discord region based analysis to improve data utility of privately published time series
ADMA'10 Proceedings of the 6th international conference on Advanced data mining and applications: Part I
Similarity matching for uncertain time series: analytical and experimental comparison
Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Querying and Mining Uncertain Spatio-Temporal Data
Shooting top-k stars in uncertain databases
The VLDB Journal — The International Journal on Very Large Data Bases
Uncertain time-series similarity: return to the basics
Proceedings of the VLDB Endowment
Preserving Privacy in Time Series Data Mining
International Journal of Data Warehousing and Mining
Protection of consumer data in the smart grid compliant with the German smart metering guideline
Proceedings of the first ACM workshop on Smart energy grid security
Monitoring web browsing behavior with differential privacy
Proceedings of the 23rd international conference on World wide web
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In this paper we study the trade-offs between time series compressibility and partial information hiding and their fundamental implications on how we should introduce uncertainty about individual values by perturbing them. More specifically, if the perturbation does not have the same compressibility properties as the original data, then it can be detected and filtered out, reducing uncertainty. Thus, by making the perturbation "similar" to the original data, we can both preserve the structure of the data better, while simultaneously making breaches harder. However, as data become more compressible, a fraction of the uncertainty can be removed if true values are leaked, revealing how they were perturbed. We formalize these notions, study the above trade-offs on real data and develop practical schemes which strike a good balance and can also be extended for on-the-fly data hiding in a streaming environment.