Workshop Theme and Topics

The enormous computation, communication and storage capabilities of the state-of-the-art computing paradigms such as cloud computing, Internet of Things (IoTs) and edge computing, have enabled a variety of large-scale applications and services that generate big data. The main and ultimate goal of the collection and storage of the big data is to extract knowledge, intelligence and insights for our decision-makings. Traditional computational intelligence algorithms need to be significantly revised or new computational intelligence algorithms have to be designed in order to make use of the scalable and distributed computing infrastructure mentioned above for big data analytics. However, the characteristics of such infrastructural platforms like ubiquitous access and multi-tenant pose unprecedented security threats on the computational intelligence algorithms and frameworks, render users more vulnerable to privacy leakage and misuse when attempting to extract rich information from big data, and challenge the trust management of the numerous computing services and diverse data sources for computational intelligence. Hence, it is high time to investigate the privacy, security and trust (PST) issues occur in computation intelligence to cater for the era of cloud/edge computing and big data.

This workshop invites authors to submit original manuscripts that demonstrate and explore current advances in all related areas. Topics of interest include, but are not limited to:

  • New privacy, security and trust opportunities and challenges brought by IoT/edge/cloud to computational intelligence

  • Novel theories and modelling for privacy, security and trust

  • Privacy, security and trust in deep/reinforcement learning models

  • Privacy-preserving big data publishing

  • Privacy-preserving data mining and machine learning

  • Privacy, security and trust issues in federated/collaborative machine learning

  • Secure and scalable machine learning

  • Privacy, security and trust issues in Smart-X technologies

  • Computational intelligence for information security and privacy

  • Security and trust management for computational intelligence frameworks

  • Blockchain for computational intelligence privacy, security and trust

  • Secure hardware design and implementation for computational intelligence

  • Real-world applications for privacy, security and trust based on computational intelligence

  • Information hiding and encryption in computational intelligence

  • Security and privacy issues, trends, and challenges in cloud/edge and IoTs

Submission Guideline

Submission portal:

Prospective authors are cordially invited to submit full/short papers up to 8 pages in length plus references. Papers submitted to the workshop must be written in English, in PDF format, conforming to the CEUR-WS format and the guidelines can be found at (two-column style, with page numbers). The paper should be submitted through the EasyChair submission portal specified above. The authors must anonymize their submissions, and all identifying attributes must be removed to allow for double-blind review. Submitted papers will be evaluated according to their originality, technical content, style, clarity, and relevance to the workshop. Submissions must be original work and should not be under submission to other venues at the time of review.

Accepted workshop papers will be included in a CIKM companion volume published by At least one of the authors of the accepted papers must register for the workshop for the paper to be included into the workshop proceedings. The accepted papers will be invited for presentation during the workshop. High quality accepted workshop papers with significant revision and extension would be further recommended to special issues in the following associated SCI/SCIE indexed journals.
  • Special Issue on "Privacy, Security, and Trust in Computational Intelligence" in Computational Intelligence (Wiley, Impact Factor 2.330), Call for Papers
  • Special Issue on "Collaborative Big Data Management and Analytics in Complex Systems with Edge" in Complexity (Impact Factor 2.833), Call for Papers
  • More to be added ...