BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//132.216.98.100//NONSGML kigkonsult.se iCalcreator 2.20.4//
BEGIN:VEVENT
UID:20260514T082442EDT-5299ksiXX3@132.216.98.100
DTSTAMP:20260514T122442Z
DESCRIPTION:The seminar will start with an introduction to general concepts
  of machine learning followed by two research directions. The first resear
 ch direction is to illustrate how to use AI for malware analysis. Assembly
  code analysis is one of the critical processes for mitigating the exponen
 tially increasing threats from malicious software. However\, it is a manua
 lly intensive and time-consuming process even for experienced reverse engi
 neers. An effective and efficient assembly code clone search engine can gr
 eatly reduce the effort of this process. The second research direction is 
 on authorship analysis for crime investigation. The objective is to identi
 fy the author or infer the author's characteristics based on their writing
  style.\n\nRegister\n\nSpeaker\n\nProf. Benjamin Fung is a Canada Research
  Chair in Data Mining for Cybersecurity\, a Full Professor of the School o
 f Information Studies (SIS) at McGill University\, and an Associate Editor
  of Elsevier Sustainable Cities and Society (SCS). He received a Ph.D. deg
 ree in computing science from Simon Fraser University in 2007. Collaborati
 ng closely with the national defense\, transportation\, and healthcare sec
 tors\, he has published over 180 refereed articles that span across the re
 search forums of data mining\, machine learning\, privacy protection\, and
  cybersecurity with over 17\,000 citations and h-index 60. His data mining
  works in crime investigation and authorship analysis have been reported b
 y media\, including the New York Times\, BBC\, CBC\, etc. Prof. Fung is a 
 licensed professional engineer in software engineering. See his research w
 ebsite http://dmas.lab.mcgill.ca/fung for more information.\n\n\n
DTSTART:20250404T170000Z
DTEND:20250404T180000Z
LOCATION:Online<br><b>Language of Delivery</b>: English
SUMMARY:AI for Malware and Authorship Analysis
URL:https://www.mcgill.ca/continuingstudies/channels/event/ai-malware-and-a
 uthorship-analysis-363876
END:VEVENT
END:VCALENDAR