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Results 1 - 10
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15,260
Calibrating noise to sensitivity in private data analysis
- In Proceedings of the 3rd Theory of Cryptography Conference
, 2006
"... Abstract. We continue a line of research initiated in [10, 11] on privacypreserving statistical databases. Consider a trusted server that holds a database of sensitive information. Given a query function f mapping databases to reals, the so-called true answer is the result of applying f to the datab ..."
Abstract
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Cited by 649 (60 self)
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the ith row of the database and g maps data-base rows to [0, 1]. We extend the study to general functions f, proving that privacy can be preserved by calibrating the standard deviation of the noise according to the sensitivity of the function f. Roughly speaking, this is the amount that any single
Smooth sensitivity and sampling in private data analysis
- In STOC
, 2007
"... 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 ..."
Abstract
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Cited by 173 (16 self)
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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
Attribute-based encryption for fine-grained access control of encrypted data
- In Proc. of ACMCCS’06
, 2006
"... As more sensitive data is shared and stored by third-party sites on the Internet, there will be a need to encrypt data stored at these sites. One drawback of encrypting data, is that it can be selectively shared only at a coarse-grained level (i.e., giving another party your private key). We develop ..."
Abstract
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Cited by 522 (23 self)
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As more sensitive data is shared and stored by third-party sites on the Internet, there will be a need to encrypt data stored at these sites. One drawback of encrypting data, is that it can be selectively shared only at a coarse-grained level (i.e., giving another party your private key). We
k-anonymity: a model for protecting privacy.
- International Journal on Uncertainty, Fuzziness and Knowledge-based Systems,
, 2002
"... Consider a data holder, such as a hospital or a bank, that has a privately held collection of person-specific, field structured data. Suppose the data holder wants to share a version of the data with researchers. How can a data holder release a version of its private data with scientific guarantees ..."
Abstract
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Cited by 1313 (15 self)
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Consider a data holder, such as a hospital or a bank, that has a privately held collection of person-specific, field structured data. Suppose the data holder wants to share a version of the data with researchers. How can a data holder release a version of its private data with scientific
TaintDroid: An Information-Flow Tracking System for Realtime Privacy Monitoring on Smartphones
, 2010
"... Today’s smartphone operating systems fail to provide users with adequate control and visibility into how third-party applications use their private data. We present TaintDroid, an efficient, system-wide dynamic taint tracking and analysis system for the popular Android platform that can simultaneous ..."
Abstract
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Cited by 527 (26 self)
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Today’s smartphone operating systems fail to provide users with adequate control and visibility into how third-party applications use their private data. We present TaintDroid, an efficient, system-wide dynamic taint tracking and analysis system for the popular Android platform that can
Security without identification: transaction systems to make Big Brother obsolete
"... The large-scale automated transaction systems of the near future can be designed to protect the privacy and maintain the security of both individuals and organizations. DAVID CHAUM Computerization is robbing individuals of the ability to monitor and control the ways information about them is used. A ..."
Abstract
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Cited by 505 (3 self)
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. As organizations in both the private and the public sectors routinely exchange such information, individ.uals have no way of knowing if the information is inaccurate, obsolete, or otherwise inappropriate. The foundation is being laid for a dossier society, in which computers could be used to infer individuals
Pricing Private Data
"... We consider a market where buyers can access unbiased samples of private data by appropriately compensating the individuals to whom the data corresponds (the sellers) according to their privacy attitudes. We show how bundling the buyers’ demand can decrease the price that buyers have to pay per data ..."
Abstract
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Cited by 1 (0 self)
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We consider a market where buyers can access unbiased samples of private data by appropriately compensating the individuals to whom the data corresponds (the sellers) according to their privacy attitudes. We show how bundling the buyers’ demand can decrease the price that buyers have to pay per
Composable memory transactions
- In Symposium on Principles and Practice of Parallel Programming (PPoPP
, 2005
"... Atomic blocks allow programmers to delimit sections of code as ‘atomic’, leaving the language’s implementation to enforce atomicity. Existing work has shown how to implement atomic blocks over word-based transactional memory that provides scalable multiprocessor performance without requiring changes ..."
Abstract
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Cited by 509 (43 self)
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leaving the block. This paper takes a four-pronged approach to improving performance: (1) we introduce a new ‘direct access ’ implementation that avoids searching thread-private logs, (2) we develop compiler optimizations to reduce the amount of logging (e.g. when a thread accesses the same data
A firm foundation for private data analysis
- Commun. ACM
"... In the information realm, loss of privacy is usually associated with failure to control access to information, to control the flow of information, or to control the purposes for which information is employed. Differential privacy arose in a context in which ensuring privacy is a challenge even if al ..."
Abstract
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Cited by 139 (3 self)
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if all these control problems are solved: privacy-preserving statistical analysis of data. The problem of statistical disclosure control – revealing accurate statistics about a set of respondents while preserving the privacy of individuals – has a venerable history, with an extensive literature spanning
Building Decision Tree Classifier on Private Data
- IN PROCEEDINGS OF THE IEEE INTERNATIONAL CONFERENCE ON PRIVACY, SECURITY AND DATA MINING
, 2002
"... This paper studies how to build a decision tree classifier under the following scenario: a database is vertically partitioned into two pieces, with one piece owned by Alice and the other piece owned by Bob. Alice and Bob want to build a decision tree classifier based on such a database, but due to t ..."
Abstract
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Cited by 136 (5 self)
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to the privacy constraints, neither of them wants to disclose their private pieces to the other party or to any third party. We present a protocol that allows Alice and Bob to conduct such a classifier building without having to compromise their privacy. Our protocol uses an untrusted third-party server
Results 1 - 10
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15,260
