International Workshop on Privacy, Security and Trust in Computational Intelligence (PSTCI2021)

Xuyun Zhang, Deepak Puthal, Chi Yang, Guanfeng Liu, Kim Kwang Raymond Choo, Hongzhi Yin

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

While being a lasting theme, privacy, security, and trust (PST) has been increasingly important in recent days due to the pervasive (but more prone) computation infrastructure and deep (but more intrusive) data analytics, and has been hugely demanded from governments, companies, and individuals. This workshop aims at providing a forum for researchers, practitioners and developers from different background areas such as computational intelligence, data privacy and cyber security, trust management, cloud computing, edge computing, Internet of Things, big data analytics, machine learning and data mining, knowledge discovery to exchange the latest experience, research ideas and synergic research and development on fundamental issues and applications about privacy, security and trust issues in computational intelligence.

Original languageBritish English
Title of host publicationCIKM 2021 - Proceedings of the 30th ACM International Conference on Information and Knowledge Management
Pages4886-4887
Number of pages2
ISBN (Electronic)9781450384469
DOIs
StatePublished - 26 Oct 2021
Event30th ACM International Conference on Information and Knowledge Management, CIKM 2021 - Virtual, Online, Australia
Duration: 1 Nov 20215 Nov 2021

Publication series

NameInternational Conference on Information and Knowledge Management, Proceedings

Conference

Conference30th ACM International Conference on Information and Knowledge Management, CIKM 2021
Country/TerritoryAustralia
CityVirtual, Online
Period1/11/215/11/21

Keywords

  • and trust
  • big data
  • computational intelligence
  • machine learning
  • privacy
  • security

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