June 4 Deadline for submissions extended to June 15th.
May 23 Authors of accepted short and full papers will be invited to submit to a Special Feature (Issue) in the Journal of Spatial Information Science (Open call for papers forthcoming).
May 15 We are excited to annouce that Dr. Benjamin I. P. Rubinstein, Associate Professor, School of Computing & Information Systems, University of Melbourne will give a keynote presentation on topics of privacy and security related to his work in machine learning, deanonymization, and health care medical records.
Location privacy has been a topic of research for many years but has recently seen a resurgence in interest. This renewed interest is driven by recent advances in location-enabled devices, sensors and context-aware technology, and the broader Internet of Things (IoT). The data generated via these devices are being collected, analyzed, and synthesized at an unprecedented rate. While much of these data are used in the advancement of products or services, many individuals are unaware of the information that is being collected, or how it is being used. The resulting information extracted from these personal data have contributed to significant advances in domain such as location recommendations or fitness/health services, but these advances often come at the cost of location privacy. This workshop is aimed at facilitating a discussion surrounding current methods and techniques related to location privacy as well as the social, political, etc. implications of sharing or preserving location privacy. Further, this workshop invites contributions and discussion related to methods and techniques for securing location information and preserving the privacy of geospatial data.
Topics of Interest
Topics of interest for the workshop include, but are not limited to:
- Context-aware mobile applications
- Obfuscation techniques
- Educational approaches to location privacy
- Policy implications of personal location information
- Role of location in personal relationship development
- Geosocial media implications
- Credibility, trust, and expertise related to location information
- Tools and systems for preserving or securing private information
- Techniques for sharing private location information
- Methods for securing location information
- Place-based data privacy
- Individual vs. group privacy preservation
- Gamification techniques
- Next-generation location-based services
- Marketplaces for location data
We invite two types of submissions for this workshop:
- Novel research contributions (6-8 pages)
- Vision / work-in-progress papers (3-6 pages)
Submissions must be original and not be under review elsewhere. Acceptance will be based on relevance to the workshop, technical quality, originality, and potential impact, as well as clarity of presentation. All submitted research papers will be reviewed by at least 3 referees and vision papers will be reviewed by a minimum of 2 referees. Papers should be formatted according to the LaTeX (or Doc) LNCS template.
Authors of accepted papers will have the option of publication through CEUR-WS and/or submission to a special issue/feature on Geospatial Privacy and Security in the Journal of Spatial Information Science. The open call for special issue papers is forethcoming.
In addition, ALL registered workshop participants will be invited to give a 5 minute, ignite style, lightning presentation on a subject related to the workshop topic.
All submissions should be made through easychair at https://easychair.org/conferences/?conf=lopas18.
To register for the workshop, please visit the GIScience Conference registration page.
Important All workshop participants are expected to adhere to the same code of conduct outlined by the main conference organizers. Please visit the Conference Code of Conduct page for further information.
Dr. Benjamin I. P. Rubinstein
Associate Professor, School of Computing & Information Systems, University of Melbourne
Dr. Benjamin Rubinstein actively researches topics in machine learning, security & privacy, databases such as adversarial learning, differential privacy and record linkage. Prior to joining the University of Melbourne in 2013, he enjoyed four years in the research divisions of Microsoft, Google, Intel and Yahoo! (all in the United States), followed by a short stint at IBM Research Australia. As a full-time Researcher at Microsoft Research, Silicon Valley, Dr. Rubinstein shipped production systems for entity resolution in Bing and the Xbox360; his research has helped identify and plug side-channel attacks against the popular Firefox browser, and deanonymise an unprecedented Australian Medicare data release, prompting introduction of the Re-identification Offence Bill 2016. Since joining Melbourne in 2013, he has led $2.0m in awarded competitive funding ($1.2m per CI). His work has been recognised through an Australian Research Council DECRA award, and a Young Tall Poppy Science award.