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*** OUR SINCERE APOLOGIES IF YOU RECEIVE MULTIPLE COPIES OF THIS
ANNOUNCEMENT
***
——————————————————————————————————————
========================================================================
CALL FOR PAPER

The 2018 International Workshop on Privacy, Security and Trust in
Computational Intelligence (PSTCI 2018), in conjunction with IEEE
TrustCom-18, August 01 - 03, 2018, New York, USA.
Website: https://sites.google.com/site/pstci2018/home

Key dates:
Submission Deadline: 07th May 2018
Authors Notification: 15th May 2018
Camera-ready Due: 15th June 2018
Conference Start: 01st August 2018

Submission site:
https://easychair.org/conferences/?conf=pstci2018

========================================================================
Paper Submission Guidelines

Papers submitted to the symposium should be written in English conforming
to the IEEE Conference Proceedings Format (8.5" x 11", Two-Column). The
paper should be submitted through the symposium EasyChair Submission
System. Prospective authors are invited to submit full papers up to 6 pages
in length and authors are allowed to purchase up to 2 extra pages.

Accepted and presented papers will be included in the IEEE Conference
Proceedings published by IEEE CS CPS and submitted to IEEE Xplore.
Submitting a paper to the symposium means that, if the paper is accepted,
at least one author should attend the symposium and present the paper. High
quality accepted workshop papers with significant revision and extension
could be further recommended to special issues in the following SCI/SCIE
indexed journals: Security and Communication Networks (Impact Factor:
1.067, also CCF Ranking C), Journal of Organizational and End User
Computing (Impact Factor: 0.759), etc.

Paper submission page: https://easychair.org/conferences/?conf=pstci2018

========================================================================
Introduction

The enormous computation, communication and storage capabilities of the
state-of-the-art computing paradigms such as cloud computing, Internet of
Things (IoTs) and fog computing, have enabled a variety of large-scale
applications and services that generate big data sets. The main and
ultimate goal of the collection and storage of the big data is to extract
the 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 when
extracting 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 the high time to investigate the
privacy, security and trust issues in computation intelligence in the era
of cloud/fog computing and big data.

This workshop aims at providing a forum for researchers, practitioners, and
developers from different background areas such as computational
intelligence, data privacy and security, trust management, cloud computing,
fog 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. The symposium solicits high quality research results in all
related areas.


Scope and Topics

The objective of this symposium is to invite authors to submit original
manuscripts that demonstrate and explore current advances in all aspects of
privacy, security, and trust in computational intelligence. The symposium
solicits novel papers on a broad range of topics, including but not limited
to:

    New challenges brought by IoT/fog/cloud to computational intelligence
    New theories and modelling for privacy, security, and trust
    Privacy, security, and trust in deep learning models
    Privacy-preserving big data mining / data publishing
    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
    Secure hardware design and implementation for computational intelligence
    Real-world applications of computational intelligence for privacy,
security, and trust
    Information hiding and encryption
    Security issues and challenges in cloud, edge, fog, and IoT

========================================================================


Program Co-Chairs
Xuyun Zhang, University of Auckland
Yuan Yuan, Michigan State University
Liangfu Lu, Tianjin University

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