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<b style="font-size: 13px;" class="">PSTrustAI 2020</b><br style="" class="">
<span style="" class="">Special Session on Privacy, Security and Trust in Artificial Intelligence</span><br style="" class="">
<br style="" class="">
<div class=""><span style="" class="">at the 12</span><span style="" class="">th</span><span style="" class=""> Asian Conference on Intelligent</span><span style="" class=""> </span><span style="" class="">Information and Database Systems (ACIIDS 2020)</span><br style="" class="">
<div class=""><span style="" class="">Phuket, Thailand, March 23-26, 2020</span><br style="" class="">
<span style="" class="">Conference website: </span><a href="http://www.aciids.pwr.edu.pl/" style="" class="">http://www.aciids.pwr.edu.pl/ </a><br class="">
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Objectives and topics<br class="">
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Breakthroughs in Artificial Intelligence (AI) combined with big data and high-performance computing has seen the emergence of society-changing AI applications. However, autonomous decision-making and the black-box design of Machine Learning (ML) make the adoption
of AI systems complicated and debates about privacy, threats, and vulnerabilities have to be raised, discussed and solutions have to be proposed. Moreover, the scientific challenges are interlinked with regulatory questions: Companies, governments, and business
sectors often rely on regulations and standards to ensure secure and safe use, but also to build trust with the customers. This workshop offers researchers and regulators the opportunity to discuss privacy, security, and trust of AI systems while identifying
new directions and approaches. The scope of the PSTrustAI includes, but is not limited to the following topics:<br class="">
<br class="">
<div class=""><span class="Apple-tab-span" style="white-space:pre"></span>• Privacy-preserving machine learning<br class="">
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<div class=""><span class="Apple-tab-span" style="white-space:pre"></span>• Threats and vulnerabilities of training data<br class="">
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<div class=""><span class="Apple-tab-span" style="white-space:pre"></span>• Model attacks and attack mitigation<br class="">
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<div class=""><span class="Apple-tab-span" style="white-space:pre"></span>• Privacy attacks on machine learning models<br class="">
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<div class=""><span class="Apple-tab-span" style="white-space:pre"></span>• Anonymization and de-anonymization techniques<br class="">
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<div class=""><span class="Apple-tab-span" style="white-space:pre"></span>• Explainable AI and transparent AI<br class="">
</div>
<div class=""><span class="Apple-tab-span" style="white-space:pre"></span>• Analysis of machine learning models<br class="">
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<div class=""><span class="Apple-tab-span" style="white-space:pre"></span>• Visualization of machine learning models<br class="">
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<div class=""><span class="Apple-tab-span" style="white-space:pre"></span>• Trustworthy AI, trustworthiness, and trust concepts <br class="">
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<div class=""><span class="Apple-tab-span" style="white-space:pre"></span>• Network-based machine learning<br class="">
</div>
<div class=""><span class="Apple-tab-span" style="white-space:pre"></span>• AI systems as complex networks<br class="">
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<div class=""><span class="Apple-tab-span" style="white-space:pre"></span>• Machine learning in complex networks<br class="">
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<div class=""><span class="Apple-tab-span" style="white-space:pre"></span>• Gap analysis between research and standardization<br class="">
</div>
<div class=""><span class="Apple-tab-span" style="white-space:pre"></span>• Regulatory challenges of AI systems<br class="">
</div>
<div class=""><span class="Apple-tab-span" style="white-space:pre"></span>• AI technical standardization<br class="">
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<div class=""><span class="Apple-tab-span" style="white-space:pre"></span>• Data and privacy governance<br class="">
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Important dates<br class="">
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Submission of papers: 15 October 2019<br class="">
Notification of acceptance: 15 November 2019<br class="">
Camera-ready papers: 1 December 2019<br class="">
Registration & payment: 15 December 2019<br class="">
Conference date: 23-26 March 2020<br class="">
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Submission<br class="">
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All contributions should be original and not published elsewhere or intended to be published during the review period. Authors are invited to submit their papers electronically in pdf format, through EasyChair. All the special sessions are centralized as tracks
in the same conference management system as the regular papers. Therefore, to submit a paper please activate the following link and select the track: PSTrustAI 2020: Special Session on Privacy, Security and Trust in Artificial Intelligence.<br class="">
<br class="">
<a href="https://easychair.org/conferences/?conf=aciids" class="">https://easychair.org/conferences/?conf=aciids</a>2020<br class="">
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Authors are invited to submit original previously unpublished research papers written in English, of up to 12 pages, strictly following the LNCS/LNAI format guidelines. Authors can download the Latex (recommended) or Word templates available at Springer's web
site. Submissions not following the format guidelines will be rejected without review. To ensure high quality, all papers will be thoroughly reviewed by the EAML 2020 Program Committee. All accepted papers must be presented by one of the authors who must register
for the conference and pay the fee. The conference proceedings will be published by Springer in the prestigious series LNCS/LNAI (indexed by ISI CPCI-S, included in ISI Web of Science, EI, ACM Digital Library, dblp, Google Scholar, Scopus, etc.).<br class="">
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Special Session Organizers<br class="">
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Prof. Pascal Bouvry<br class="">
University of Luxembourg, Luxembourg</div>
<div class="">E-mail: <a href="mailto:pascal.bouvry@uni.lu" class="">pascal.bouvry@uni.lu</a></div>
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Dr. Matthias R. Brust<br class="">
University of Luxembourg, Luxembourg</div>
<div class="">E-mail: <a href="mailto:matthias.brust@uni.lu" class="">matthias.brust@uni.lu</a></div>
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Dr. Grégoire Danoy<br class="">
University of Luxembourg, Luxembourg<br class="">
E-mail: g<a href="mailto:regoire.danoy@uni.lu" class="">regoire.danoy@uni.lu</a></div>
<div class=""><br class="">
Prof. El-Ghazali Talbi<br class="">
University of Lille, INRIA, France<br class="">
E-mail: <a href="mailto:el-ghazali.talbi@univ-lille.fr" class="">el-ghazali.talbi@univ-lille.fr</a><br class="">
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