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SUMMARY:Federated Deep Learning for Intrusion Detection in Smart Critical 
 Infrastructure - Segun Popoola\, Anglia Ruskin University
DTSTART:20241112T140000Z
DTEND:20241112T150000Z
UID:TALK221410@talks.cam.ac.uk
CONTACT:Tina Marjanov
DESCRIPTION:The integration of the Internet of Things (IoT) into smart cri
 tical infrastructure has significantly enhanced monitoring\, control\, and
  efficiency. However\, this integration introduces new cybersecurity risks
 \, as IoT devices can become vulnerable points for attackers targeting ess
 ential services such as electricity\, water\, and transportation. Addressi
 ng these risks requires robust intrusion detection systems to monitor and 
 mitigate potential cyber threats. This talk explores the application of de
 ep learning and federated learning techniques to enhance intrusion detecti
 on in IoT-enabled smart critical infrastructure. It will also cover the ch
 allenges and security implications of using Artificial Intelligence (AI) i
 n the cybersecurity of smart critical infrastructure and discuss current s
 olutions to ensure AI systems remain safe\, secure\, and resilient against
  cyber-attacks.\n\nZoom link: https://cam-ac-uk.zoom.us/j/82810963958?pwd=
 ukzuxkUpQRIPDaekbPb706z6ZUPn0E.1
LOCATION:Webinar &amp\; LT2\, Computer Laboratory\, William Gates Building
 .
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