![]() |
| |||||||||||||||
PPDMA 2016 : IEEE IJCNN/WCCI 2016 Special Session on “Privacy-preserving in Data Mining and Applications” | |||||||||||||||
Link: http://www.ppdma2016.conferences.academy | |||||||||||||||
| |||||||||||||||
Call For Papers | |||||||||||||||
*** IJCNN/WCCI 2016 Special Session Call for Papers ***
========================================================================================== IJCNN/WCCI 2016 Special Session on "Privacy-preserving in Data Mining and Applications" URL: http://www.ppdma2016.conferences.academy/ Submission System: http://www.wcci2016.org/submission.php Accepted papers will appear in the IJCNN/WCCI 2016 proceedings to be published by IEEE. ========================================================================================== -----~*******~-------- Important Dates -----~*******~-------- Paper Submission Due: 15/01/2016 Author Notification Due: 15/03/2016 Camera Ready Due: 15/04/2016 -----~*******~-------- Conference Scope -----~*******~-------- Over the past two decades, digital information collected by corporations, organizations and governments has resulted in huge number of datasets, and the speed of such data collection has increased dramatically over the last a few years. A data collector, also known as a curator, is in charge of releasing and publishing data for data mining and some applications. However, most of the collected datasets are personally related and contain private or sensitive information. Even though curators can apply several simple anonymization techniques, there is still a high probability that the sensitive information of individuals has a high probability to be disclosed. Privacy-preserving has therefore become an urgent issue that needs to be addressed. Research communities have proposed various methods to preserve privacy and have designed a number of metrics to evaluate the privacy level of these methods. The interest in this area is very high and the notion is spanning in a range of research areas, ranging from the privacy community, to the data science communities including machine learning, data mining, statistics and learning theory. Much work has been conducted in a number of application domains, including social network, online education, recommender systems and tourism. A significant number of new technologies and applications have appeared in the privacy-preserving research area. We believe that it is a good time to cover these topics in the special session, which will include recent advances and applications in the privacy preserving research in data mining and diverse applications. -----~*******~-------- Topics of Interest -----~*******~-------- Papers are invited in the areas below, but do not exclude research in the general areas of the topic headings. (1) Privacy-preserving in Data Mining - Privacy-preserving in Big Data - Privacy-preserving data analysis - Privacy-preserving in database systems - Miscellaneous privacy issues (2) Privacy-preserving in Applications - Privacy-preserving in cloud/mobile/wireless communications - Privacy-preserving in E-learning and e-government - Privacy-preserving in applications and services - Privacy-preserving in services -----~*******~-------- Paper Submissions -----~*******~-------- Manuscripts submitted to special sessions should be done through the paper submission website of IEEE WCCI 2016. http://www.wcci2016.org/submission.php Please make sure that papers submitted to their special session clearly indicate the name of the special session the paper belongs to. Main Research Topic: "Tf: Privacy-Preserving in Data Mining and Applications" All papers submitted to special sessions will be subject to the same peer-review procedure as the regular papers. -----~*******~-------- Organizers -----~*******~-------- Dr Tianqing Zhu, Deakin University, Australia Dr Gang Li, Deakin University, Australia A/Prof. Ping Xiong, Zhongnan University of Economic and Law, China |
|