Using Stylometry to Attribute Programmers and Writers

Friday, January 26, 2018 - 11:00am EST

  • Location:2 Metrotech Center, 10th floor, 10.099

Speaker: Rachel Greenstadt, Drexel University

Abstract:

In this talk, I will discuss my lab's work in the emerging field of adversarial stylometry and machine learning. Machine learning algorithms are increasingly being used in security and privacy domains, in areas that go beyond intrusion or spam detection. For example, in digital forensics, questions often arise about the authors of documents: their identity, demographic background, and whether they can be linked to other documents. The field of stylometry uses linguistic features and machine learning techniques to answer these questions. We have applied stylometry to difficult domains such as underground hacker forums, open source projects (code), and tweets. I will discuss our Doppelgänger Finder algorithm, which enables us to group Sybil accounts on underground forums and detect blogs from Twitter feeds and reddit comments. In addition, I will discuss our work attributing unknown source code and binaries.

Bio:

Dr. Rachel Greenstadt is an Associate Professor of Computer Science at Drexel University where she teaches graduate-level courses in computer security, privacy, and machine learning. She founded the Privacy, Security, and Automation Laboratory at Drexel University in 2008. She has attracted a research team of Ph.D. students and undergraduates with interests and expertise in information extraction, machine learning, agents, privacy, trust, and security.

Dr. Greenstadt’s scholarship has been recognized by the privacy research community. She is an alum of the DARPA Computer Science Study Group and a recipient of the NSF CAREER Award. Her work has received the PET Award for Outstanding Research in Privacy Enhancing Technologies and the Andreas Pfitzmann Best Student Paper Award. She currently serves as co-editor-in-chief of the journal Proceedings on Privacy Enhancing Technologies (PoPETs).  Her research has been featured in the New York Times, the New Republic, Der Spiegel, and other local and international media outlets.