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: [email protected] Pierangela Samarati, University of Milan, Italy. Email: [email protected] Abderrahim BENSLIMANE, University of Avignon, France. Email: [email protected] Shui Yu, University of Technology, Australia. E-mail: [email protected] 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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