3 citations · 3 across the 7 of their papers we have counts for
5 papers · 1 filter
Image Compression and Actionable Intelligence With Deep Neural Networks
Matthew Ciolino
If a unit cannot receive intelligence from a source due to external factors, we consider them disadvantaged users. We categorize this as a preoccupied unit working on a low connect…
Color Teams for Machine Learning Development
Josh Kalin, David Noever, Matthew Ciolino
Machine learning and software development share processes and methodologies for reliably delivering products to customers. This work proposes the use of a new teaming construct for…
A Modified Drake Equation for Assessing Adversarial Risk to Machine Learning Models
Josh Kalin, David Noever, Matthew Ciolino
Machine learning models present a risk of adversarial attack when deployed in production. Quantifying the contributing factors and uncertainties using empirical measures could assi…
Fortify Machine Learning Production Systems: Detect and Classify Adversarial Attacks
Matthew Ciolino, Josh Kalin, David Noever
Production machine learning systems are consistently under attack by adversarial actors. Various deep learning models must be capable of accurately detecting fake or adversarial in…
Black Box to White Box: Discover Model Characteristics Based on Strategic Probing
Josh Kalin, Matthew Ciolino, David Noever +1
In Machine Learning, White Box Adversarial Attacks rely on knowing underlying knowledge about the model attributes. This works focuses on discovering to distrinct pieces of model i…