1 citations · 2 across the 4 of their papers we have counts for
4 papers
Empirical Analysis of Evasion and Poisoning Against Malware Data Drift Detection
Mingyue Yang, David Lie, Nicolas Papernot
As concept drift due to malware evolution presents challenges for malware classification, machine learning-based data drift detection tools are developed to mitigate this problem.…
Maximizing Information Gain in Privacy-Aware Active Learning of Email Anomalies
Mu-Huan Miles Chung, Sharon Li, Jaturong Kongmanee +7
Redacted emails satisfy most privacy requirements but they make it more difficult to detect anomalous emails that may be indicative of data exfiltration. In this paper we develop a…
Calpric: Inclusive and Fine-grain Labeling of Privacy Policies with Crowdsourcing and Active Learning
Wenjun Qiu, David Lie, Lisa Austin
A significant challenge to training accurate deep learning models on privacy policies is the cost and difficulty of obtaining a large and comprehensive set of training data. To add…
Calpric: Inclusive and Fine-grain Labeling of Privacy Policies with Crowdsourcing and Active Learning
Wenjun Qiu, David Lie, Lisa Austin
A significant challenge to training accurate deep learning models on privacy policies is the cost and difficulty of obtaining a large and comprehensive set of training data. To add…