Results 1  10
of
1,143
Output Perturbation with Query Relaxation
, 2008
"... Given a dataset containing sensitive personal information, a statistical database answers aggregate queries in a manner that preserves individual privacy. We consider the problem of constructing a statistical database using output perturbation, which protects privacy by injecting a small noise into ..."
Abstract

Cited by 13 (0 self)
 Add to MetaCart
Given a dataset containing sensitive personal information, a statistical database answers aggregate queries in a manner that preserves individual privacy. We consider the problem of constructing a statistical database using output perturbation, which protects privacy by injecting a small noise
Relationship privacy: Output perturbation for queries with joins
 In ACM Symposium on Principles of Database Systems, 2009. [13] Yossi
"... We study privacypreserving query answering over data containing relationships. A social network is a prime example of such data, where the nodes represent individuals and edges represent relationships. Nearly all interesting queries over social networks involve joins, and for such queries, existing ..."
Abstract

Cited by 53 (8 self)
 Add to MetaCart
, existing output perturbation algorithms severely distort query answers. We propose an algorithm that significantly improves utility over competing techniques, typically reducing the error bound from polynomial in the number of nodes to polylogarithmic. The algorithm is, to the best of our knowledge
Polynomialtime Attack on Output Perturbation Sanitizers for Realvalued Databases
 Journal of Privacy and Confidentiality
"... Output Perturbation is one of several strategies in the area of Statistical Disclosure Control (SDC), also known as Private Data Analysis. The general problem in SDC consists of releasing valuable information about individuals in a databasewhile preserving their privacy. Examples of this include da ..."
Abstract

Cited by 1 (0 self)
 Add to MetaCart
Output Perturbation is one of several strategies in the area of Statistical Disclosure Control (SDC), also known as Private Data Analysis. The general problem in SDC consists of releasing valuable information about individuals in a databasewhile preserving their privacy. Examples of this include
RealTime Computing Without Stable States: A New Framework for Neural Computation Based on Perturbations
"... A key challenge for neural modeling is to explain how a continuous stream of multimodal input from a rapidly changing environment can be processed by stereotypical recurrent circuits of integrateandfire neurons in realtime. We propose a new computational model for realtime computing on timevar ..."
Abstract

Cited by 469 (38 self)
 Add to MetaCart
time from the current state of such recurrent neural circuit information about current and past inputs that may be needed for diverse tasks. Stable internal states are not required for giving a stable output, since transient internal states can be transformed by readout neurons into stable target outputs
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 socalled true answer is the result of applying f to the datab ..."
Abstract

Cited by 649 (60 self)
 Add to MetaCart
to the database. To protect privacy, the true answer is perturbed by the addition of random noise generated according to a carefully chosen distribution, and this response, the true answer plus noise, is returned to the user. Previous work focused on the case of noisy sums, in which f =P i g(xi), where xi denotes
Smooth Stabilization Implies Coprime Factorization
, 1989
"... This paper shows that coprime right factorizations exist for the input to state mapping of a continuous time nonlinear system provided that the smooth feedback stabilization problem be solvable for this system. In particular, it follows that feedback linearizable systems admit such factorizations. I ..."
Abstract

Cited by 472 (62 self)
 Add to MetaCart
. In order to establish the result a Lyapunovtheoretic definition is proposed for "bounded input bounded output" stability. The main technical fact proved relates the notion of stabilizability studied in the state space nonlinear control literature to a notion of stability under bounded control
Securitycontrol methods for statistical databases: a comparative study
 ACM Computing Surveys
, 1989
"... This paper considers the problem of providing security to statistical databases against disclosure of confidential information. Securitycontrol methods suggested in the literature are classified into four general approaches: conceptual, query restriction, data perturbation, and output perturbation. ..."
Abstract

Cited by 416 (0 self)
 Add to MetaCart
This paper considers the problem of providing security to statistical databases against disclosure of confidential information. Securitycontrol methods suggested in the literature are classified into four general approaches: conceptual, query restriction, data perturbation, and output perturbation
Calibrated Probabilistic Mesoscale Weather Field Forecasting: The Geostatistical Output Perturbation (GOP) Method
, 2003
"... Probabilistic weather forecasting consists of finding a joint probability distribution for future weather quantities or events. It is typically done by using a numerical weather prediction model, perturbing the inputs to the model in various ways, often depending on data assimilation, and running th ..."
Abstract

Cited by 27 (15 self)
 Add to MetaCart
without the vast data and computing resources of national weather centers. Instead, we propose a simpler method which breaks with much previous practice by perturbing the outputs, or deterministic forecasts, from the model. Forecast errors are modeled using a geostatistical model, and ensemble members
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

Cited by 173 (16 self)
 Add to MetaCart
the noise magnitude to the smooth sensitivity of f on the database x — a measure of variability of f in the neighborhood of the instance x. The new framework greatly expands the applicability of output perturbation, a technique for protecting individuals ’ privacy by adding a small amount of random noise
Optimization of Perturb and Observe Maximum Power Point Tracking Method
"... Abstract—Maximum power point tracking (MPPT) techniques are used in photovoltaic (PV) systems to maximize the PV array output power by tracking continuously the maximum power point (MPP) which depends on panels temperature and on irradiance conditions. The issue of MPPT has been addressed in differe ..."
Abstract

Cited by 116 (2 self)
 Add to MetaCart
Abstract—Maximum power point tracking (MPPT) techniques are used in photovoltaic (PV) systems to maximize the PV array output power by tracking continuously the maximum power point (MPP) which depends on panels temperature and on irradiance conditions. The issue of MPPT has been addressed
Results 1  10
of
1,143