Boosting the accuracy of differentially private histograms through consistency
Proceedings of the VLDB Endowment
Resisting structural re-identification in anonymized social networks
The VLDB Journal — The International Journal on Very Large Data Bases
Personalized social recommendations: accurate or private
Proceedings of the VLDB Endowment
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Neighborhood-privacy protected shortest distance computing in cloud
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
Sharing graphs using differentially private graph models
Proceedings of the 2011 ACM SIGCOMM conference on Internet measurement conference
Introducing ScaleGraph: an X10 library for billion scale graph analytics
Proceedings of the 2012 ACM SIGPLAN X10 Workshop
Differentially private search log sanitization with optimal output utility
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
Privacy-Preserving EM algorithm for clustering on social network
PAKDD'12 Proceedings of the 16th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part I
Privacy preservation of user history graph
WISTP'12 Proceedings of the 6th IFIP WG 11.2 international conference on Information Security Theory and Practice: security, privacy and trust in computing systems and ambient intelligent ecosystems
Proceedings of the 7th ACM Symposium on Information, Computer and Communications Security
Differentially private graphical degree sequences and synthetic graphs
PSD'12 Proceedings of the 2012 international conference on Privacy in Statistical Databases
Differentially private data analysis of social networks via restricted sensitivity
Proceedings of the 4th conference on Innovations in Theoretical Computer Science
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 Guide to Differential Privacy Theory in Social Network Analysis
ASONAM '12 Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)
Recursive mechanism: towards node differential privacy and unrestricted joins
Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data
Privacy-preserving data exploration in genome-wide association studies
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Outsourcing shortest distance computing with privacy protection
The VLDB Journal — The International Journal on Very Large Data Bases
A near-optimal algorithm for differentially-private principal components
The Journal of Machine Learning Research
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We describe an efficient algorithm for releasing a provably private estimate of the degree distribution of a network. The algorithm satisfies a rigorous property of differential privacy, and is also extremely efficient, running on networks of 100 million nodes in a few seconds. Theoretical analysis shows that the error scales linearly with the number of unique degrees, whereas the error of conventional techniques scales linearly with the number of nodes. We complement the theoretical analysis with a thorough empirical analysis on real and synthetic graphs, showing that the algorithm's variance and bias is low, that the error diminishes as the size of the input graph increases, and that common analyses like fitting a power-law can be carried out very accurately.