Upcoming events

The computer science colloquium takes place on Mondays from 11:15 a.m. - 12:15 p.m.

This week's talk is a part of the Cray Distinguished Speaker Series. This series was established in 1981 by an endowment from Cray Research and brings distinguished visitors to the Department of Computer Science & Engineering every year.

This week's speaker, Elisa Bertino (Purdue University), will be giving a talk titled "Security of Cellular networks".

Abstract

As the world moves to 5G cellular networks and next-generation is being envisioned , security and privacy are of paramount importance and new tools are needed to ensure them. In the talk, after discussing motivating trends in wireless communications, we present LTEInspector a model-based testing approach for cellular network protocols. LTEInspector combines a symbolic model checker and a cryptographic protocol verifier in the symbolic attacker model. Using it, we have uncovered 10 new attacks along with 9 prior attacks, categorized into three abstract classes (i.e., security, user privacy, and disruption of service), in three procedures of 4G LTE. Notable among the findings is the authentication relay attack that enables an adversary to spoof the location of a legitimate user to the core network without possessing appropriate credentials. To ensure that the exposed attacks pose real threats and are indeed realizable in practice, 8 of the 10 new attacks have been validated and their accompanying adversarial assumptions have been put through a real testbed. We then overview on-going research projects.

Bio

Elisa Bertino is Samuel Conte professor of Computer Science at Purdue University. She serves as Director of the Purdue Cyberspace Security Lab (Cyber2Slab). Prior to joining Purdue, she was a professor and department head at the Department of Computer Science and Communication of the University of Milan. She has been a visiting researcher at the IBM Research Laboratory in San Jose (now Almaden), at Rutgers University, at Telcordia Technologies. She has also held visiting professor positions at the Singapore National University and the Singapore Management University.  Her main research interests include security, privacy, database systems, distributed systems, and sensor networks. Her recent research focuses on cybersecurity and privacy of cellular networks and IoT systems, and on edge analytics for cybersecurity.  Elisa Bertino is a Fellow member of  IEEE, ACM, and AAAS. She received the 2002 IEEE Computer Society Technical Achievement Award for “For outstanding contributions to database systems and database security and advanced data management systems”, the 2005 IEEE Computer Society Tsutomu Kanai Award for “Pioneering and innovative research contributions to secure distributed systems”, and the 2019-2020 ACM Athena Lecturer Award.

The computer science colloquium takes place on Mondays from 11:15 a.m. - 12:15 p.m. 

This week's talk is a part of the Cray Distinguished Speaker Series. This series was established in 1981 by an endowment from Cray Research and brings distinguished visitors to the Department of Computer Science & Engineering every year.

This week's speaker, David Evans (University of Virginia), will be giving a talk titled "On Leaky Models and Unintended Inferences".

Abstract:

Machine learning offers the promise to train models that perform surprisingly well on a wide range of tasks, merely by using massive computing power and generic training algorithms on available data sets. It is an open question, however, what else those models might learn about their training data, and how an adversary with some access to the model may be able to reveal it. In this talk, I will discuss a variety of inference risks associated with machine-trained models, with a particular focus on surprising (and potentially harmful) things a model may reveal not just about individual training records but about the overall distribution of its training data. This includes attacks an adversary may use to learn statistical properties about the training distribution and about whether certain kinds of data are or are not included, and the potential for an adversary to use a model to make sensitive inferences about individuals, even for attributes not directly related to the task and regardless of whether those individuals are included the training data. I’ll conclude with some thoughts on why defending against these types of attacks is hard, and what we might learn about how we should be training and exposing models.

Bio:

David Evans (https://www.cs.virginia.edu/evans/) is a Professor of Computer Science at the University of Virginia where he leads research on security and privacy (https://uvasrg.github.io/) with a recent focus on adversarial machine learning and inference risks in machine learning, and teaches courses on a wide variety of topics including biology, ethics, economics, and theory of computing. He is the author of an open computer science textbook (https://computingbook.org) and a children's book on combinatorics and computability (https://dori-mic.org) and co-author of a book on secure computation (https://securecomputation.org/). He won the Outstanding Faculty Award from the State Council of Higher Education for Virginia and is Program Co-Chair for the 2022 and 2023 IEEE European Symposia on Security and Privacy. He was Program Co-Chair for the 24th ACM Conference on Computer and Communications Security (CCS 2017) and the 30th (2009) and 31st (2010) IEEE Symposia on Security and Privacy, where he initiated the Systematization of Knowledge (SoK) papers (https://oaklandsok.github.io/). He has SB, SM and PhD degrees in Computer Science from MIT and has been a faculty member at the University of Virginia since 1999.

The computer science colloquium takes place on Mondays from 11:15 a.m. - 12:15 p.m. More details about the fall 2022 series will be provided at the beginning of the semester. 

The computer science colloquium takes place on Mondays from 11:15 a.m. - 12:15 p.m. More details about the fall 2022 series will be provided at the beginning of the semester. 

RSVP today!.

During each session, the graduate staff will review:

• Requirements (general)
• Applying
• Prerequisite requirements
• What makes a strong applicant
• Funding
• Resources
• Common questions
• Questions from attendees

Students considering the following programs should attend:

• Computer Science M.S.
• Computer Science M.C.S.
• Computer Science Ph.D.
• Data Science M.S.
• Data Science Post-Baccalaureate Certificate
  
   

The computer science colloquium takes place on Mondays from 11:15 a.m. - 12:15 p.m. More details about the fall 2022 series will be provided at the beginning of the semester. 

The computer science colloquium takes place on Mondays from 11:15 a.m. - 12:15 p.m. More details about the fall 2022 series will be provided at the beginning of the semester. 

The computer science colloquium takes place on Mondays from 11:15 a.m. - 12:15 p.m. More details about the fall 2022 series will be provided at the beginning of the semester. 

The computer science colloquium takes place on Mondays from 11:15 a.m. - 12:15 p.m. More details about the fall 2022 series will be provided at the beginning of the semester. 

The computer science colloquium takes place on Mondays from 11:15 a.m. - 12:15 p.m. More details about the fall 2022 series will be provided at the beginning of the semester.