[Om-announce] CFP: Big Data Mining and Analytics Special Issue on Privacy-Preserving Data Mining for Artificial Intelligence of Things

[Youyang Qu]

Dear Professor ,



I believe this email finds you and your loved ones safe and healthy.


Artificial Intelligence of Things (AIoT) is experiencing unimaginable fast
booming with the popularization of end devices and advanced machine
learning and data processing techniques. An increasing volume of data is
being collected every single second to enable Artificial Intelligence (AI)
on the Internet of Things (IoT). The explosion of data brings significant
benefits to various intelligent industries to provide predictive services
and research institutes to advance human knowledge in data-intensive
fields. To make the best use of the collected data, various data
mining techniques have been deployed to extract data patterns. In classic
scenarios, the data collected from IoT devices is directly sent to cloud
servers for processing using diverse methods such as training machine
learning models. However, the network between cloud servers and massive end
devices may not be stable due to irregular bursts of traffic, weather, etc.
Therefore, autonomous data mining that is self-organized by a group of
local devices to maintain ongoing and robust AI services plays a growing
important role for critical IoT infrastructures. Privacy issues become more
concerning in this scenario. The data transmitted via autonomous networks
are publicly accessible by all internal participants, which increases the
risk of exposure. Besides, data mining techniques may reveal sensitive
information from the collected data. Various attacks, such as inference
attacks, are emerging and evolving to breach sensitive data due to its
great financial benefits. Motivated by this, it is essential to devise
novel privacy-preserving autonomous data mining solutions for AIoT. In this
Special Issue, we aim to gather state-of-art advances in privacy-preserving
data mining and autonomous data processing solutions for AIoT. Topics
include, but are not limited to, the following:

   - Privacy-preserving federated learning for AIoT
   - Differentially private machine learning for AIoT
   - Personalized privacy-preserving data mining
   - Decentralized machine learning paradigms for autonomous data mining
   using blockchain
   - AI-enhanced edge data mining for AIoT
   - AI and blockchain empowered privacy-preserving big data analytics for
   AIoT
   - Anomaly detection and inference attack defense for AIoT
   - Privacy protection measurement metrics
   - Zero trust architectures for privacy protection management
   - Privacy protection data mining and analysis via blockchain-enabled
   digital twin


The authors are requested to submit their full research papers complying
with the general scope of the journal. The submitted papers will undergo a
peer review process before they can be accepted. Notification of acceptance
will be communicated as we progress with the review process.

*SUBMISSION GUIDELINES*
Papers submitted to this journal for possible publication must be original
and must not be under consideration for publication in any other journals.
Prospective authors should submit an electronic copy of their
completed manuscript to *https://mc03.manuscriptcentral.com/bdma
<https://mc03.manuscriptcentral.com/bdma>* with manuscript type as “Special
Issue on Privacy-Preserving Data Mining for Artificial Intelligence of
Things”. Further information on the journal is available at:
*http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=8254253
<http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=8254253>*.

*IMPORTANT DATES*
Deadline for submissions: June 30, 2022
1st round of acceptance notification: July 15, 2022
Submission of revised papers: August 15, 2022
2nd round of acceptance notification: September 15, 2022
Publication online (tentative): November 15, 2022


*GUEST EDITORS*
Youyang Qu, Deakin University, Australia. E-mail: y.qu at deakin.edu.au
Pierangela Samarati, University of Milan, Italy. Email:
pierangela.samarati at unimi.it
Abderrahim BENSLIMANE, University of Avignon, France. Email:
abderrahim.benslimane at univ-avignon.fr
Shui Yu, University of Technology, Australia. E-mail: shui.yu at uts.edu.au



Thank you for your time and support.

With warm regards,

Youyang

---

Youyang Qu,

Research Scientist

Commonwealth Scientific and Industrial Research Organization, Australia
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