Events Calendar

CS Colloquium: Mohamed Hussein (USC ISI) - Securing Machine Vision Models

Speaker: Mohamed Hussein, USC ISI

Talk Title: Securing Machine Vision Models

Abstract: Machine vision has evolved dramatically over the past decade, thanks to the deep learning revolution. Despite their remarkable performance, often surpassing humans, machine vision models are vulnerable to different types of attacks. This talk will focus on two types of attacks as well as methods to secure machine vision models against them. The first is presentation (or more commonly known as spoofing) attacks on biometric authentication systems, in which the attacker presents a fake physical instrument to the system, such as a printed face image, either to conceal their true identity or impersonate a different identity. I will show that combining the power of deep learning with multi-spectral sensing can effectively address this problem by distinguishing spoofing instruments from bona fide presentations. For the challenging makeup attack, I will show that using multi-spectral data, we can construct an image of a person without the applied makeup, and hence reveal their true identity. The second type of attack is adversarial attacks. In this type of attack, imperceptible perturbations can be applied to the input of a machine vision model to alter the model's prediction. I will present a new non-linear activation function, named Difference of Mirrored Exponential terms (DOME), which has the property of inducing compactness to the embedding space of a deep learning model. We found that combining the usage of DOME with adversarial training can boost the robustness against state of the art adversarial attacks. I will conclude by discussing my perspective on the challenges ahead regarding the security of machine vision models.

This lecture satisfies requirements for CSCI 591: Research Colloquium

Biography: Dr. Mohamed E. Hussein is a Computer Scientist and a Research Lead at USC ISI. Dr. Hussein obtained his Ph.D. degree in Computer Science from the University of Maryland at College Park, MD, USA in 2009. Then, he spent close to two years as an Adjunct Member Research Staff at Mitsubishi Electric Research Labs, Cambridge, MA, before moving to Alexandria University, Egypt, as a faculty member. Prior to joining ISI in 2017, he spent three years at Egypt-Japan University of Science and Technology (E-JUST), Alexandria, Egypt. During his time as a faculty member in Egypt, Dr. Hussein was the PI/Co-PI on multiple industry and government funded research projects on Sign Language Recognition and Crowd Scene Analysis. He is currently a Co-PI for ISI's projects under IARPA's Odin and BRIAR programs and DARPA's GARD program.

Host: CS Department

Webcast: https://usc.zoom.us/j/98761669161

Location: Ronald Tutor Hall of Engineering (RTH) - 105

WebCast Link: https://usc.zoom.us/j/98761669161

Audiences: Everyone Is Invited

Contact: Cherie Carter