Unmasking the Vulnerabilities of Deep Learning Models: A Multi-Dimensional Analysis of Adversarial Attacks and Defenses

Firuz Juraev, Mohammed Abuhamad, Eric Chan-Tin, George K. Thiruvathukal, Tamer Abuhmed

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Original languageEnglish
Title of host publication2024 Silicon Valley Cybersecurity Conference, SVCC 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350383140
DOIs
StatePublished - 2024
Event2024 Silicon Valley Cybersecurity Conference, SVCC 2024 - Seoul, Korea, Republic of
Duration: Jun 17 2024Jun 19 2024

Publication series

Name2024 Silicon Valley Cybersecurity Conference, SVCC 2024

Conference

Conference2024 Silicon Valley Cybersecurity Conference, SVCC 2024
Country/TerritoryKorea, Republic of
CitySeoul
Period6/17/246/19/24

ASJC Scopus Subject Areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Hardware and Architecture
  • Information Systems and Management
  • Safety, Risk, Reliability and Quality

Keywords

  • Adversarial Perturbations
  • Black-box Attacks
  • Deep Learning
  • Defensive Techniques
  • Threat Analysis

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