In the age of big data, privacy and security have unique significances, which lead to the traditional techniques and models cannot cover the connotation of the privacy and security of big data. Therefore, it is necessary to rethink and reorient the real problems. Although many models and perspectives have been around for quite some time, emerging applications in big distributed system that connect society, networks, mobility and personalization, put new requirements on privacy and security with respect to distributed data management. Privacy and security risks widely exist in different stages of the data life cycle, from massive data collection, data storage to data analysis, stimulating a wide spectrum of privacy and security research topics.
Nowadays, data privacy and security is one of the most active and intriguing areas in computer science with many real challenges to be addressed. Some of the challenges include evaluating and defining privacy, quantifying privacy and security, infrastructure security, mining new privacy and security attacks, privacy-preserving big data mining and learning, big data release with security and privacy protection, and applying new technologies of privacy and security to various emerging applications, such as mobile crowd sensing, mobile social network, Internet of Things, and cloud computing, etc.
In this workshop, we focus on the privacy and security challenges that arise from the use of enterprise and other privacy sensitive data in big data ecosystem. Our aim is to bring together people from the privacy research community and security research community, and provide a forum for researchers, practitioners and others interested in this area, to exchange new results and perspectives on privacy and security in big data ecosystem. Authors from both academia and industry are invited to submit papers presenting novel research on the topics of interest.
Topics of Interest include (but not limited to)