71 citations · 201 across the 6 of their papers we have counts for
7 papers
Managing your Private and Public Data: Bringing down Inference Attacks against your Privacy
Salman Salamatian, Amy Zhang, Flavio du Pin Calmon +5
We propose a practical methodology to protect a user's private data, when he wishes to publicly release data that is correlated with his private data, in the hope of getting some u…
Privacy Tradeoffs in Predictive Analytics
Stratis Ioannidis, Andrea Montanari, Udi Weinsberg +3
Online services routinely mine user data to predict user preferences, make recommendations, and place targeted ads. Recent research has demonstrated that several private user attri…
Recommending with an Agenda: Active Learning of Private Attributes using Matrix Factorization
Smriti Bhagat, Udi Weinsberg, Stratis Ioannidis +1
Recommender systems leverage user demographic information, such as age, gender, etc., to personalize recommendations and better place their targeted ads. Oftentimes, users do not v…
Mixture Models of Endhost Network Traffic
John Mark Agosta, Jaideep Chandrashekar, Mark Crovella +2
In this work we focus on modeling a little studied type of traffic, namely the network traffic generated from endhosts. We introduce a parsimonious parametric model of the marginal…
CARE: Content Aware Redundancy Elimination for Disaster Communications on Damaged Networks
Udi Weinsberg, Athula Balachandran, Nina Taft +3
During a disaster scenario, situational awareness information, such as location, physical status and images of the surrounding area, is essential for minimizing loss of life, injur…
Private Decayed Sum Estimation under Continual Observation
Jean Bolot, Nadia Fawaz, S. Muthukrishnan +2
In monitoring applications, recent data is more important than distant data. How does this affect privacy of data analysis? We study a general class of data analyses - computing pr…
Learning in a Large Function Space: Privacy-Preserving Mechanisms for SVM Learning
Benjamin I. P. Rubinstein, Peter L. Bartlett, Ling Huang +1
Several recent studies in privacy-preserving learning have considered the trade-off between utility or risk and the level of differential privacy guaranteed by mechanisms for stati…