HCI for Cybersecurity, Privacy and Trust Best Paper Award

HCI for Cybersecurity, Privacy and Trust Best Paper Award. Details in text following the image.
 

Best Paper Award for the 1st International Conference on HCI for Cybersecurity, Privacy and Trust, in the context of HCI International 2019, 16-31 July 2019, Orlando, FL, USA

 

Certificate for best paper award of the 1st International Conference on HCI for Cybersecurity, Privacy and Trust. Details in text following the image

Certificate for Best Paper Award of the 1st International Conference on HCI for Cybersecurity, Privacy and Trust
conferred to

Alexander Berman (Texas A&M University, USA) and
Celeste Lyn Paul (U.S. Department of Defense, USA)

for the paper entitled

"Making Sense of Darknet Markets: Automatic Inference of Semantic Classifications from Unconventional Multimedia Datasets"

Presented in the context of
HCI International 2019
16-31 July 2019, Orlando, FL, USA

Paper Abstract
"Darknet Markets are a hotbed of illicit trade and are difficult for law enforcement to monitor and analyze. Topic Modeling has been a popular method to semantically analyze market listings, but lacks the ability to infer the information-rich visual semantics of images embedded within these listings. In this paper we present a relatively fast method using unsupervised and self-supervised machine learning methods to infer image semantics from large, unstructured multimedia corpora, and demonstrate how it may aid analysts in investigating the content of Darknet Markets. "

The full paper is available through SpringerLink, provided that you have proper access rights.