3 citations · 3 across the 4 of their papers we have counts for
4 papers
Trojans in Artificial Intelligence (TrojAI) Final Report
Kristopher W. Reese, Taylor Kulp-McDowall, Michael Majurski +68
The Intelligence Advanced Research Projects Activity (IARPA) launched the TrojAI program to confront an emerging vulnerability in modern artificial intelligence: the threat of AI T…
AI Model Utilization Measurements For Finding Class Encoding Patterns
Peter Bajcsy, Antonio Cardone, Chenyi Ling +5
This work addresses the problems of (a) designing utilization measurements of trained artificial intelligence (AI) models and (b) explaining how training data are encoded in AI mod…
Baseline Pruning-Based Approach to Trojan Detection in Neural Networks
Peter Bajcsy, Michael Majurski
This paper addresses the problem of detecting trojans in neural networks (NNs) by analyzing systematically pruned NN models. Our pruning-based approach consists of three main steps…
Scientific Calculator for Designing Trojan Detectors in Neural Networks
Peter Bajcsy, Nicholas J. Schaub, Michael Majurski
This work presents a web-based interactive neural network (NN) calculator and a NN inefficiency measurement that has been investigated for the purpose of detecting trojans embedded…