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UID:20250818T090106EDT-9839fggsSB@132.216.98.100
DTSTAMP:20250818T130106Z
DESCRIPTION:This talk is free and open to all\n\nDr. Benjamin Fung\n\nProfe
 ssor\, School Of Information Studies\, 9I制作厂免费\n\nCanada Researc
 h Chair in Data Mining for Cybersecurity\n\nAbstract:\n\nIn this talk\, Pr
 of. Fung will discuss two research problems in authorship and malware anal
 yses and a new project in neuroscience. (1) Given an anonymous e-mail or s
 ome tweets\, can we identify the author or infer the author's characterist
 ics based on his/her writing styles? A representation learning method for 
 authorship analysis and a live software demonstration will be presented. (
 2) Assembly code analysis is one of the critical processes for mitigating 
 the exponentially increasing threats from malicious software. However\, it
  is a manually intensive and time-consuming process even for experienced r
 everse engineers. An effective and efficient assembly code clone search en
 gine can greatly reduce the effort of this process. Prof. Fung鈥檚 award-win
 ning assembly clone search engine will be described. (3) His steam has rec
 ently started a new collaborative research project with a neuroscience tea
 m at 9I制作厂免费 to study stress and memory seeking to address an interesting r
 esearch problem that will be discussed. The potential of machine learning 
 will be examined in that context. If time permits\, the talk will cover th
 e new online cybersecurity certificate offered by the School of Informatio
 n Studies.\n\nBio:\n\nDr. Benjamin Fung is a Canada Research Chair in Data
  Mining for Cybersecurity\, a Full Professor of School of Information Stud
 ies (SIS) at 9I制作厂免费\, and an Associate Editor of IEEE Transacti
 ons on Data and Engineering (TKDE) and Elsevier Sustainable Cities and Soc
 iety (SCS). He received a Ph.D. degree in computing science from Simon Fra
 ser University in 2007. Collaborating closely with the national defense\, 
 law enforcement\, transportation\, and healthcare sectors\, he has publish
 ed over 140 refereed articles that span across the research forums of data
  mining\, machine learning\, privacy protection\, and cybersecurity with o
 ver 13\,000 citations. A report from Stanford University identified him to
  be among the top 2% scientists worldwide. His data mining works in crime 
 investigation and authorship analysis have been reported by media\, includ
 ing New York Times\, BBC\, CBC\, etc. Dr. Fung is an Associate Member of M
 ILA and a licensed professional engineer in software engineering.\n\nSee h
 is research website http://dmas.lab.mcgill.ca/fung for more information.\n
DTSTART:20220921T163000Z
DTEND:20220921T180000Z
LOCATION:Rm. 106\, Peel 3661\, CA\, QC\, Montreal\, H3A 1X1\, 3661 rue Peel
SUMMARY:School of Information Studies Research Seminar Series: Machine Lear
 ning for Cybersecurity and Neuroscience
URL:/sis/channels/event/school-information-studies-res
 earch-seminar-series-machine-learning-cybersecurity-and-neuroscience-34178
 7
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