2 citations · 2 across the 4 of their papers we have counts for
6 papers
Busting the Paper Ballot: Voting Meets Adversarial Machine Learning
Kaleel Mahmood, Caleb Manicke, Ethan Rathbun +5
We show the security risk associated with using machine learning classifiers in United States election tabulators. The central classification task in election tabulation is decidin…
Game Theoretic Mixed Experts for Combinational Adversarial Machine Learning
Ethan Rathbun, Kaleel Mahmood, Sohaib Ahmad +2
Recent advances in adversarial machine learning have shown that defenses considered to be robust are actually susceptible to adversarial attacks which are specifically customized t…
Privacy Attacks Against Biometric Models with Fewer Samples: Incorporating the Output of Multiple Models
Sohaib Ahmad, Benjamin Fuller, Kaleel Mahmood
Authentication systems are vulnerable to model inversion attacks where an adversary is able to approximate the inverse of a target machine learning model. Biometric models are a pr…
Resist : Reconstruction of irises from templates
Sohaib Ahmad, Christopher Geiger, Benjamin Fuller
Iris recognition systems transform an iris image into a feature vector. The seminal pipeline segments an image into iris and non-iris pixels, normalizes this region into a fixed-di…
ThirdEye: Triplet Based Iris Recognition without Normalization
Sohaib Ahmad, Benjamin Fuller
Most iris recognition pipelines involve three stages: segmenting into iris/non-iris pixels, normalization the iris region to a fixed area, and extracting relevant features for comp…
Unconstrained Iris Segmentation using Convolutional Neural Networks
Sohaib Ahmad, Benjamin Fuller
The extraction of consistent and identifiable features from an image of the human iris is known as iris recognition. Identifying which pixels belong to the iris, known as segmentat…