Abstract Number:
1123
Submission Type:
Invited Paper Session
Participants:
Xiaoming Huo (1), Bin Yu (2), Xiaoming Huo (1), Bo Li (3), Radha Poovendran (4), Jie Gao (5), Joao Hespanha (6)
Institutions:
(1) Georgia Institute of Technology, School of Industrial & Systems Engineering, N/A, (2) University of California at Berkeley, N/A, (3) University of Chicago, Chicago, IL, (4) University of Washington, Seattle, WA, (5) Rutgers University, Piscataway, NJ, (6) University of California, Santa Barbara (UCSB), Santa Barbara, CA
Chair:
Xiaoming Huo
Georgia Institute of Technology, School of Industrial & Systems Engineering
Co-Organizer:
Bin Yu
University of California at Berkeley
Session Organizer:
Xiaoming Huo
Georgia Institute of Technology, School of Industrial & Systems Engineering
Speaker(s):
Bo Li
University of Chicago
Session Description:
Cybersecurity is crucial in today's society. The recent internet disruption at the University of Michigan underscores its significance. This session will feature experts in cybersecurity from the newly NSF-funded AI institute (https://action.ucsb.edu). We will discuss the applications of statistics and machine learning in cybersecurity, aiming to foster collaboration between statistical research and cybersecurity initiatives.
Sponsors:
IMS 3
Section on Statistical Computing 2
Section on Statistical Learning and Data Science 1
Theme:
Statistics and Data Science: Informing Policy and Countering Misinformation
Yes
Applied
Yes
Estimated Audience Size
Medium (80-150)
I have read and understand that JSM participants must abide by the Participant Guidelines.
Yes
I understand and have communicated to my proposed speakers that JSM participants must register and pay the appropriate registration fee by June 1, 2024. The registration fee is nonrefundable.
I understand