Secret sharing homomorphisms: keeping shares of a secret secret
Proceedings on Advances in cryptology---CRYPTO '86
Summary cache: a scalable wide-area Web cache sharing protocol
Proceedings of the ACM SIGCOMM '98 conference on Applications, technologies, architectures, and protocols for computer communication
Communications of the ACM
A method to compress and anonymize packet traces
IMW '01 Proceedings of the 1st ACM SIGCOMM Workshop on Internet Measurement
New directions in traffic measurement and accounting
Proceedings of the 2002 conference on Applications, technologies, architectures, and protocols for computer communications
A signal analysis of network traffic anomalies
Proceedings of the 2nd ACM SIGCOMM Workshop on Internet measurment
Data streams: algorithms and applications
SODA '03 Proceedings of the fourteenth annual ACM-SIAM symposium on Discrete algorithms
ICNP '02 Proceedings of the 10th IEEE International Conference on Network Protocols
Tools for privacy preserving distributed data mining
ACM SIGKDD Explorations Newsletter
Fast accurate computation of large-scale IP traffic matrices from link loads
SIGMETRICS '03 Proceedings of the 2003 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Automatically inferring patterns of resource consumption in network traffic
Proceedings of the 2003 conference on Applications, technologies, architectures, and protocols for computer communications
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
Gigascope: a stream database for network applications
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Sketch-based change detection: methods, evaluation, and applications
Proceedings of the 3rd ACM SIGCOMM conference on Internet measurement
State-of-the-art in privacy preserving data mining
ACM SIGMOD Record
Diagnosing network-wide traffic anomalies
Proceedings of the 2004 conference on Applications, technologies, architectures, and protocols for computer communications
IP forwarding anomalies and improving their detection using multiple data sources
Proceedings of the ACM SIGCOMM workshop on Network troubleshooting: research, theory and operations practice meet malfunctioning reality
Characterization of network-wide anomalies in traffic flows
Proceedings of the 4th ACM SIGCOMM conference on Internet measurement
Private collaborative forecasting and benchmarking
Proceedings of the 2004 ACM workshop on Privacy in the electronic society
Aberrant Behavior Detection in Time Series for Network Monitoring
LISA '00 Proceedings of the 14th USENIX conference on System administration
Space efficient mining of multigraph streams
Proceedings of the twenty-fourth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Sketching streams through the net: distributed approximate query tracking
VLDB '05 Proceedings of the 31st international conference on Very large data bases
IMC '05 Proceedings of the 5th ACM SIGCOMM conference on Internet Measurement
Privacy-Preserving graph algorithms in the semi-honest model
ASIACRYPT'05 Proceedings of the 11th international conference on Theory and Application of Cryptology and Information Security
NetScope: traffic engineering for IP networks
IEEE Network: The Magazine of Global Internetworking
Privacy-preserving performance measurements
Proceedings of the 2006 SIGCOMM workshop on Mining network data
Report from the clean slate network research post-sigcomm 2006 workshop
ACM SIGCOMM Computer Communication Review
Building a prototype for network measurement virtual observatory
Proceedings of the 3rd annual ACM workshop on Mining network data
Multiple target localisation in sensor networks with location privacy
ESAS'07 Proceedings of the 4th European conference on Security and privacy in ad-hoc and sensor networks
SEPIA: privacy-preserving aggregation of multi-domain network events and statistics
USENIX Security'10 Proceedings of the 19th USENIX conference on Security
Managing power conservation in wireless networks
ADMA'10 Proceedings of the 6th international conference on Advanced data mining and applications - Volume Part II
A statistical data mining approach in bacteriology for bacterial identification
International Journal of Data Analysis Techniques and Strategies
TMA'11 Proceedings of the Third international conference on Traffic monitoring and analysis
Privacy-preserving distributed network troubleshooting—bridging the gap between theory and practice
ACM Transactions on Information and System Security (TISSEC)
Practical private information aggregation in large networks
NordSec'10 Proceedings of the 15th Nordic conference on Information Security Technology for Applications
Federated flow-based approach for privacy preserving connectivity tracking
Proceedings of the ninth ACM conference on Emerging networking experiments and technologies
Computer Networks: The International Journal of Computer and Telecommunications Networking
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The rapid growth of the Internet over the last decade has been startling. However, efforts to track its growth have often fallen afoul of bad data --- for instance, how much traffic does the Internet now carry? The problem is not that the data is technically hard to obtain, or that it does not exist, but rather that the data is not shared. Obtaining an overall picture requires data from multiple sources, few of whom are open to sharing such data, either because it violates privacy legislation, or exposes business secrets. Likewise, detection of global Internet health problems is hampered by a lack of data sharing. The approaches used so far in the Internet, e.g. trusted third parties, or data anonymization, have been only partially successful, and are not widely adopted.The paper presents a method for performing computations on shared data without any participants revealing their secret data. For example, one can compute the sum of traffic over a set of service providers without any service provider learning the traffic of another. The method is simple, scalable, and flexible enough to perform a wide range of valuable operations on Internet data.