Security-control methods for statistical databases: a comparative study
ACM Computing Surveys (CSUR)
On the concentration of multivariate polynomials with small expectation
Random Structures & Algorithms
Tools for privacy preserving distributed data mining
ACM SIGKDD Explorations Newsletter
Revealing information while preserving privacy
Proceedings of the twenty-second ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Limiting privacy breaches in privacy preserving data mining
Proceedings of the twenty-second ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Optimal Time Bounds for Approximate Clustering
Machine Learning
A spectral algorithm for learning mixture models
Journal of Computer and System Sciences - Special issue on FOCS 2002
Aggregating inconsistent information: ranking and clustering
Proceedings of the thirty-seventh annual ACM symposium on Theory of computing
Practical privacy: the SuLQ framework
Proceedings of the twenty-fourth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
ACM SIGKDD Explorations Newsletter
The Effectiveness of Lloyd-Type Methods for the k-Means Problem
FOCS '06 Proceedings of the 47th Annual IEEE Symposium on Foundations of Computer Science
ICALP'06 Proceedings of the 33rd international conference on Automata, Languages and Programming - Volume Part II
Toward privacy in public databases
TCC'05 Proceedings of the Second international conference on Theory of Cryptography
Our data, ourselves: privacy via distributed noise generation
EUROCRYPT'06 Proceedings of the 24th annual international conference on The Theory and Applications of Cryptographic Techniques
Calibrating noise to sensitivity in private data analysis
TCC'06 Proceedings of the Third conference on Theory of Cryptography
A learning theory approach to non-interactive database privacy
STOC '08 Proceedings of the fortieth annual ACM symposium on Theory of computing
Composition attacks and auxiliary information in data privacy
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Distributed Private Data Analysis: Simultaneously Solving How and What
CRYPTO 2008 Proceedings of the 28th Annual conference on Cryptology: Advances in Cryptology
New Efficient Attacks on Statistical Disclosure Control Mechanisms
CRYPTO 2008 Proceedings of the 28th Annual conference on Cryptology: Advances in Cryptology
Output perturbation with query relaxation
Proceedings of the VLDB Endowment
Adversarial-knowledge dimensions in data privacy
The VLDB Journal — The International Journal on Very Large Data Bases
Universally utility-maximizing privacy mechanisms
Proceedings of the forty-first annual ACM symposium on Theory of computing
Proceedings of the forty-first annual ACM symposium on Theory of computing
Differential privacy and robust statistics
Proceedings of the forty-first annual ACM symposium on Theory of computing
Relationship privacy: output perturbation for queries with joins
Proceedings of the twenty-eighth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Privacy-Preserving Data Publishing
Foundations and Trends in Databases
Proceedings of the 18th ACM conference on Information and knowledge management
Proceedings of the 16th ACM conference on Computer and communications security
Asymptotically Optimal and Private Statistical Estimation
CANS '09 Proceedings of the 8th International Conference on Cryptology and Network Security
Differential privacy with compression
ISIT'09 Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 4
Differential privacy for collaborative security
Proceedings of the Third European Workshop on System Security
Differential privacy: a survey of results
TAMC'08 Proceedings of the 5th international conference on Theory and applications of models of computation
An ad omnia approach to defining and achieving private data analysis
PinKDD'07 Proceedings of the 1st ACM SIGKDD international conference on Privacy, security, and trust in KDD
On the geometry of differential privacy
Proceedings of the forty-second ACM symposium on Theory of computing
Optimizing linear counting queries under differential privacy
Proceedings of the twenty-ninth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Universally optimal privacy mechanisms for minimax agents
Proceedings of the twenty-ninth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Towards an axiomatization of statistical privacy and utility
Proceedings of the twenty-ninth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Airavat: security and privacy for MapReduce
NSDI'10 Proceedings of the 7th USENIX conference on Networked systems design and implementation
Distance makes the types grow stronger: a calculus for differential privacy
Proceedings of the 15th ACM SIGPLAN international conference on Functional programming
Differentially private combinatorial optimization
SODA '10 Proceedings of the twenty-first annual ACM-SIAM symposium on Discrete Algorithms
Differential privacy and the fat-shattering dimension of linear queries
APPROX/RANDOM'10 Proceedings of the 13th international conference on Approximation, and 14 the International conference on Randomization, and combinatorial optimization: algorithms and techniques
Does differential privacy protect terry gross' privacy?
PSD'10 Proceedings of the 2010 international conference on Privacy in statistical databases
Some additional insights on applying differential privacy for numeric data
PSD'10 Proceedings of the 2010 international conference on Privacy in statistical databases
Resisting structural re-identification in anonymized social networks
The VLDB Journal — The International Journal on Very Large Data Bases
P4P: practical large-scale privacy-preserving distributed computation robust against malicious users
USENIX Security'10 Proceedings of the 19th USENIX conference on Security
Limits of computational differential privacy in the client/server setting
TCC'11 Proceedings of the 8th conference on Theory of cryptography
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Differentially private data cubes: optimizing noise sources and consistency
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
iReduct: differential privacy with reduced relative errors
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Privacy-aware data management in information networks
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Privacy-preserving statistical estimation with optimal convergence rates
Proceedings of the forty-third annual ACM symposium on Theory of computing
Evaluating Laplace Noise Addition to Satisfy Differential Privacy for Numeric Data
Transactions on Data Privacy
Differentially Private Empirical Risk Minimization
The Journal of Machine Learning Research
Formal Verification of Differential Privacy for Interactive Systems (Extended Abstract)
Electronic Notes in Theoretical Computer Science (ENTCS)
How much is enough? choosing ε for differential privacy
ISC'11 Proceedings of the 14th international conference on Information security
Sharing graphs using differentially private graph models
Proceedings of the 2011 ACM SIGCOMM conference on Internet measurement conference
Differential privacy for location pattern mining
Proceedings of the 4th ACM SIGSPATIAL International Workshop on Security and Privacy in GIS and LBS
SIAM Journal on Computing
Approximately optimal mechanism design via differential privacy
Proceedings of the 3rd Innovations in Theoretical Computer Science Conference
Secure distributed computation of anonymized views of shared databases
ACM Transactions on Database Systems (TODS)
A rigorous and customizable framework for privacy
PODS '12 Proceedings of the 31st symposium on Principles of Database Systems
GUPT: privacy preserving data analysis made easy
SIGMOD '12 Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data
Differential privacy in data publication and analysis
SIGMOD '12 Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data
Beating randomized response on incoherent matrices
STOC '12 Proceedings of the forty-fourth annual ACM symposium on Theory of computing
Unconditional differentially private mechanisms for linear queries
STOC '12 Proceedings of the forty-fourth annual ACM symposium on Theory of computing
Integrating historical noisy answers for improving data utility under differential privacy
Proceedings of the 15th International Conference on Extending Database Technology
A differentially private estimator for the stochastic Kronecker graph model
Proceedings of the 2012 Joint EDBT/ICDT Workshops
A workflow for differentially-private graph synthesis
Proceedings of the 2012 ACM workshop on Workshop on online social networks
Detecting dependencies in an anonymized dataset
Proceedings of the International Conference on Advances in Computing, Communications and Informatics
PrivBasis: frequent itemset mining with differential privacy
Proceedings of the VLDB Endowment
Functional mechanism: regression analysis under differential privacy
Proceedings of the VLDB Endowment
Adaptive differentially private histogram of low-dimensional data
PETS'12 Proceedings of the 12th international conference on Privacy Enhancing Technologies
Differential privacy: on the trade-off between utility and information leakage
FAST'11 Proceedings of the 8th international conference on Formal Aspects of Security and Trust
On significance of the least significant bits for differential privacy
Proceedings of the 2012 ACM conference on Computer and communications security
The effectiveness of lloyd-type methods for the k-means problem
Journal of the ACM (JACM)
A framework for evaluating the smoothness of data-mining results
ECML PKDD'12 Proceedings of the 2012 European conference on Machine Learning and Knowledge Discovery in Databases - Volume Part II
Differentially private graphical degree sequences and synthetic graphs
PSD'12 Proceedings of the 2012 international conference on Privacy in Statistical Databases
Is privacy compatible with truthfulness?
Proceedings of the 4th conference on Innovations in Theoretical Computer Science
Differentially private data analysis of social networks via restricted sensitivity
Proceedings of the 4th conference on Innovations in Theoretical Computer Science
Differential private trajectory protection of moving objects
Proceedings of the Third ACM SIGSPATIAL International Workshop on GeoStreaming
On optimal differentially private mechanisms for count-range queries
Proceedings of the 16th International Conference on Database Theory
Optimal error of query sets under the differentially-private matrix mechanism
Proceedings of the 16th International Conference on Database Theory
Testing the lipschitz property over product distributions with applications to data privacy
TCC'13 Proceedings of the 10th theory of cryptography conference on Theory of Cryptography
Analyzing graphs with node differential privacy
TCC'13 Proceedings of the 10th theory of cryptography conference on Theory of Cryptography
On Learning Cluster Coefficient of Private Networks
ASONAM '12 Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)
A privacy framework: indistinguishable privacy
Proceedings of the Joint EDBT/ICDT 2013 Workshops
Differential privacy in intelligent transportation systems
Proceedings of the sixth ACM conference on Security and privacy in wireless and mobile networks
Recursive mechanism: towards node differential privacy and unrestricted joins
Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data
Publishing trajectories with differential privacy guarantees
Proceedings of the 25th International Conference on Scientific and Statistical Database Management
Privacy-preserving data exploration in genome-wide association studies
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Practical differential privacy via grouping and smoothing
Proceedings of the VLDB Endowment
The geometry of differential privacy: the sparse and approximate cases
Proceedings of the forty-fifth annual ACM symposium on Theory of computing
Differential privacy for neighborhood-based collaborative filtering
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Differential privacy for functions and functional data
The Journal of Machine Learning Research
Pufferfish: A framework for mathematical privacy definitions
ACM Transactions on Database Systems (TODS)
Membership privacy: a unifying framework for privacy definitions
Proceedings of the 2013 ACM SIGSAC conference on Computer & communications security
A near-optimal algorithm for differentially-private principal components
The Journal of Machine Learning Research
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We introduce a new, generic framework for private data analysis.The goal of private data analysis is to release aggregate information about a data set while protecting the privacy of the individuals whose information the data set contains.Our framework allows one to release functions f of the data withinstance-based additive noise. That is, the noise magnitude is determined not only by the function we want to release, but also bythe database itself. One of the challenges is to ensure that the noise magnitude does not leak information about the database. To address that, we calibrate the noise magnitude to the smoothsensitivity of f on the database x --- a measure of variabilityof f in the neighborhood of the instance x. The new frameworkgreatly expands the applicability of output perturbation, a technique for protecting individuals' privacy by adding a smallamount of random noise to the released statistics. To our knowledge, this is the first formal analysis of the effect of instance-basednoise in the context of data privacy. Our framework raises many interesting algorithmic questions. Namely,to apply the framework one must compute or approximate the smoothsensitivity of f on x. We show how to do this efficiently for several different functions, including the median and the cost ofthe minimum spanning tree. We also give a generic procedure based on sampling that allows one to release f(x) accurately on manydatabases x. This procedure is applicable even when no efficient algorithm for approximating smooth sensitivity of f is known orwhen f is given as a black box. We illustrate the procedure by applying it to k-SED (k-means) clustering and learning mixtures of Gaussians.