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SUMMARY:Assessing and Mitigating Privacy Risks in Machine Learning and Dat
 a-Intensive Environments
DTSTART;VALUE=DATE-TIME:20260714T090000Z
DTEND;VALUE=DATE-TIME:20260714T120000Z
DTSTAMP;VALUE=DATE-TIME:20260702T234225Z
UID:indico-contribution-217-1172@events.grnet.gr
DESCRIPTION:Speakers: Manolis  Terrovitis (ATHENA RC)\nThis webinar introd
 uces the key privacy challenges arising from machine learning and data-int
 ensive applications. Participants will explore the principles of data anon
 ymization\, pseudonymization\, and differential privacy\, along with commo
 n privacy attacks targeting datasets and AI models. Through practical exam
 ples and a hands-on session with the Amnesia anonymization platform\, atte
 ndees will learn how to assess and mitigate privacy risks while developing
  compliant and privacy-preserving AI solutions.\n\nhttps://events.grnet.gr
 /event/217/contributions/1172/
LOCATION:
URL:https://events.grnet.gr/event/217/contributions/1172/
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