95 citations · 855 across the 81 of their papers we have counts for
8 papers · 1 filter
Reinforcing Adversarial Robustness using Model Confidence Induced by Adversarial Training
Xi Wu, Uyeong Jang, Jiefeng Chen +2
In this paper we study leveraging confidence information induced by adversarial training to reinforce adversarial robustness of a given adversarially trained model. A natural measu…
Malware Lineage in the Wild
Irfan Ul Haq, Sergio Chica, Juan Caballero +1
Malware lineage studies the evolutionary relationships among malware and has important applications for malware analysis. A persistent limitation of prior malware lineage approache…
Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting
Samuel Yeom, Irene Giacomelli, Matt Fredrikson +1
Machine learning algorithms, when applied to sensitive data, pose a distinct threat to privacy. A growing body of prior work demonstrates that models produced by these algorithms m…
Locally Differentially Private Heavy Hitter Identification
Tianhao Wang, Ninghui Li, Somesh Jha
The notion of Local Differential Privacy (LDP) enables users to answer sensitive questions while preserving their privacy. The basic LDP frequent oracle protocol enables the aggreg…
Policy by Example: An Approach for Security Policy Specification
Adwait Nadkarni, William Enck, Somesh Jha +1
Policy specification for personal user data is a hard problem, as it depends on many factors that cannot be predetermined by system developers. Simultaneously, systems are increasi…
Analyzing the Robustness of Nearest Neighbors to Adversarial Examples
Yizhen Wang, Somesh Jha, Kamalika Chaudhuri
Motivated by safety-critical applications, test-time attacks on classifiers via adversarial examples has recently received a great deal of attention. However, there is a general la…
Optimizing Locally Differentially Private Protocols
Tianhao Wang, Jeremiah Blocki, Ninghui Li +1
Protocols satisfying Local Differential Privacy (LDP) enable parties to collect aggregate information about a population while protecting each user's privacy, without relying on a…
ROSA: R Optimizations with Static Analysis
Rathijit Sen, Jianqiao Zhu, Jignesh M. Patel +1
R is a popular language and programming environment for data scientists. It is increasingly co-packaged with both relational and Hadoop-based data platforms and can often be the mo…