Attacking RF Machine Learning Systems
Abstract
The VT Hume Center proposes to develop both foundational and applied research results aimed at blind characterization and optimal attack methods against RF machine learning systems, to include attacks on wideband (500 MHz) blind signal classification, ML-infused DSA algorithms, ML-trained behaviors generalized to match time-varying channel conditions, and specific emitter identification techniques. We will also explore battle damage assessment of an adversary’s ML-based RF system.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Oct 09, 2018
- Source ID
- N001741810005
Entities
People
- Alan J. Michaels
Organizations
- United States Navy
- Virginia Tech