“Introduction to Adversarial Machine Learning” - Michael De Lucia, Army Research Lab (ARL)

We will introduce the concept of adversarial machine learning, a technique where carefully constructed or perturbed data instances, observations, or training data can be used to cause a machine learning model, such as an image classifier, to make widely inaccurate predictions.

Michael De Lucia (Ph.D. ECE, UD, ’20; MS & BS CS, NJIT, ‘05/’06, CSSA) is a Computer Scientist at
the U.S. Army’s Applied Research Laboratory (ARL), Aberdeen Proving Ground, MD, where he
researches computer and network security, and machine learning for network security applications. Dr. De Lucia is Adjunct Professor in ECE at UD, and was an NJIT Adjunct Instructor 2006-2011.