ICNP '02 Proceedings of the 10th IEEE International Conference on Network Protocols
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
k-anonymity: a model for protecting privacy
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
A high-level programming environment for packet trace anonymization and transformation
Proceedings of the 2003 conference on Applications, technologies, architectures, and protocols for computer communications
Diagnosing network-wide traffic anomalies
Proceedings of the 2004 conference on Applications, technologies, architectures, and protocols for computer communications
The devil and packet trace anonymization
ACM SIGCOMM Computer Communication Review
SC2D: an alternative to trace anonymization
Proceedings of the 2006 SIGCOMM workshop on Mining network data
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
SSYM'00 Proceedings of the 9th conference on USENIX Security Symposium - Volume 9
Robust De-anonymization of Large Sparse Datasets
SP '08 Proceedings of the 2008 IEEE Symposium on Security and Privacy
What's going on?: learning communication rules in edge networks
Proceedings of the ACM SIGCOMM 2008 conference on Data communication
Network discovery from passive measurements
Proceedings of the ACM SIGCOMM 2008 conference on Data communication
Privacy-safe network trace sharing via secure queries
Proceedings of the 1st ACM workshop on Network data anonymization
Differentially private recommender systems: building privacy into the net
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Privacy integrated queries: an extensible platform for privacy-preserving data analysis
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
Swing: realistic and responsive network traffic generation
IEEE/ACM Transactions on Networking (TON)
Differential privacy for collaborative security
Proceedings of the Third European Workshop on System Security
Differentially private aggregation of distributed time-series with transformation and encryption
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
OSDI'08 Proceedings of the 8th USENIX conference on Operating systems design and implementation
ICALP'06 Proceedings of the 33rd international conference on Automata, Languages and Programming - Volume Part II
Calibrating noise to sensitivity in private data analysis
TCC'06 Proceedings of the Third conference on Theory of Cryptography
Algorithms for packet classification
IEEE Network: The Magazine of Global Internetworking
I know what you will do next summer
ACM SIGCOMM Computer Communication Review
Privacy-preserving distributed network troubleshooting—bridging the gap between theory and practice
ACM Transactions on Information and System Security (TISSEC)
Sharing graphs using differentially private graph models
Proceedings of the 2011 ACM SIGCOMM conference on Internet measurement conference
ACM SIGCOMM Computer Communication Review
The power of the dinur-nissim algorithm: breaking privacy of statistical and graph databases
PODS '12 Proceedings of the 31st symposium on Principles of Database Systems
Towards statistical queries over distributed private user data
NSDI'12 Proceedings of the 9th USENIX conference on Networked Systems Design and Implementation
Human mobility modeling at metropolitan scales
Proceedings of the 10th international conference on Mobile systems, applications, and services
Software abstractions for trusted sensors
Proceedings of the 10th international conference on Mobile systems, applications, and services
Keeping information safe from social networking apps
Proceedings of the 2012 ACM workshop on Workshop on online social networks
Low-rank mechanism: optimizing batch queries under differential privacy
Proceedings of the VLDB Endowment
Functional mechanism: regression analysis under differential privacy
Proceedings of the VLDB Endowment
Differentially private sequential data publication via variable-length n-grams
Proceedings of the 2012 ACM conference on Computer and communications security
On significance of the least significant bits for differential privacy
Proceedings of the 2012 ACM conference on Computer and communications security
Privacy-aware personalization for mobile advertising
Proceedings of the 2012 ACM conference on Computer and communications security
On differentially private frequent itemset mining
Proceedings of the VLDB Endowment
Linear dependent types for differential privacy
POPL '13 Proceedings of the 40th annual ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Privacy-preserving data exploration in genome-wide association studies
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Differential privacy based on importance weighting
Machine Learning
Differentially private histogram publication
The VLDB Journal — The International Journal on Very Large Data Bases
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We consider the potential for network trace analysis while providing the guarantees of "differential privacy." While differential privacy provably obscures the presence or absence of individual records in a dataset, it has two major limitations: analyses must (presently) be expressed in a higher level declarative language; and the analysis results are randomized before returning to the analyst. We report on our experiences conducting a diverse set of analyses in a differentially private manner. We are able to express all of our target analyses, though for some of them an approximate expression is required to keep the error-level low. By running these analyses on real datasets, we find that the error introduced for the sake of privacy is often (but not always) low even at high levels of privacy. We factor our learning into a toolkit that will be likely useful for other analyses. Overall, we conclude that differential privacy shows promise for a broad class of network analyses.