BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//wp-events-plugin.com//7.2.3.1//EN
TZID:Asia/Kolkata
X-WR-TIMEZONE:Asia/Kolkata
BEGIN:VEVENT
UID:108@cds.iisc.ac.in
DTSTART;TZID=Asia/Kolkata:20250303T160000
DTEND;TZID=Asia/Kolkata:20250303T170000
DTSTAMP:20250219T055255Z
URL:https://cds.iisc.ac.in/events/seminar-cds-102-march-03rd-0400-applying
 -machine-learning-to-securing-cellular-networks/
SUMMARY:{Seminar} @ CDS: #102\, March 03rd\, 04:00: "Applying Machine Learn
 ing to Securing Cellular Networks"
DESCRIPTION:\n\nACM-IISc Pullur Distinguished Computing Visitor Program\n\n
 \n\nSpeaker : Prof. Elisa Bertino\, Purdue University\, USA\nTitle : "Appl
 ying Machine Learning to Securing Cellular Networks"\nDate &amp\; Time : M
 arch 03\, 2025 (Monday)\, 04:00 PM\nVenue : # 102\, CDS Seminar Hall\n\n\n
 \nABSTRACT\n\nCellular network security is more critical than ever\, given
  the increased complexity of these networks and the numbers of application
 s that depend on them\, including telehealth\, remote education\, ubiquito
 us robotics and autonomous vehicles\, smart cities\, and Industry 4.0. In 
 order to devise more effective defenses\, a recent trend is to leverage ma
 chine learning (ML) techniques\, which have become applicable because of t
 oday advanced capabilities for collecting data as well high-performance co
 mputing systems for training of ML models. Recent large language models (L
 LMs) are also opening new interesting directions for security applications
 . In this talk\, I will first present a comprehensive threat analysis in t
 he context of 5G cellular networks to give a concrete example of the magni
 tude of the problem of cellular network security. Then\, I will present tw
 o specific applications of ML techniques for the security of cellular netw
 orks. The first application focuses on the use of natural language process
 ing techniques to the problem of detecting inconsistencies in the "natural
  language specifications" of cellular network protocols. The second applic
 ation addresses the design of an anomaly detection system able to detect t
 he presence of malicious base stations and determine the type of attack. T
 hen I'll conclude with a discussion on research directions.\n\nBIO: Elisa 
 Bertino is a Samuel Conte Distinguished Professor of Computer Science at P
 urdue University. She serves as Director of the Purdue Cyberspace Security
  Lab (Cyber2Slab). Prior to joining Purdue\, she was a professor and depar
 tment head at the Department of Computer Science and Communication of the 
 University of Milan. She has been a visiting researcher at the IBM Researc
 h Laboratory in San Jose (now Almaden)\, at Rutgers University\, at Telcor
 dia Technologies. She has also held visiting professor positions at the Si
 ngapore National University and the Singapore Management University. Her r
 ecent research focuses on security and privacy of cellular networks and Io
 T systems\, and on edge analytics for cybersecurity. Elisa Bertino is a Fe
 llow member of IEEE\, ACM\, and AAAS. She received the 2002 IEEE Computer 
 Society Technical Achievement Award for “For outstanding contributions t
 o database systems and database security and advanced data management syst
 ems”\, the 2005 IEEE Computer Society Tsutomu Kanai Award for “Pioneer
 ing and innovative research contributions to secure distributed systems”
 \, the 2019-2020 ACM Athena Lecturer Award\, and the 2021 IEEE 2021 Innova
 tion in Societal Infrastructure Award. She received an Honorary Doctorate 
 from Aalborg University in 2021 and an Honorary Research Doctorate in Comp
 uter Science from the University of Salerno in 2023. She is currently serv
 ing as ACM Vice-president.\n\nHost Faculty: Prof. Jayant Haritsa\n\n\n\nAL
 L ARE WELCOME
CATEGORIES:Events,Talks
END:VEVENT
BEGIN:VTIMEZONE
TZID:Asia/Kolkata
X-LIC-LOCATION:Asia/Kolkata
BEGIN:STANDARD
DTSTART:20240303T160000
TZOFFSETFROM:+0530
TZOFFSETTO:+0530
TZNAME:IST
END:STANDARD
END:VTIMEZONE
END:VCALENDAR