PriSMO 2013 - First International Workshop on Privacy and Security for Moving Objects (PriSMO)

Nowadays we are experiencing an explosion in the volume of data that are created by moving objects and users. Location based data are registered either explicitly, by users who share their location in location based social networks, or implicitly by GPS trackers on vehicles and RFID tags on moving objects. Often they can also be inferred by other location specific actions, like credit card charges in physical stores and usage of RFID cards in mass transit. The widespread availability of RFID chips and the developments in the the wireless com- munications have resulted to a digitized environment where user and object movement very often leaves a digital trace.
Movement data constitutes valuable information. Collecting, storing and processing move- ment data allows service providers to offer location based services to users, it facilitates transparency and accountability in goods transportation, it allows the dynamic routing of services and it enables the on-line monitoring of a plethora of commercial activities. More- over, users share their location and movement patterns with friends in social networks to coordinate their activities with a minimum overhead. Data about user and object movement is a very rich source of information with social, economical and environmental value, and it is nowadays available in such a scale, that it is considered a characteristic case of big data.
The information richness that makes movement data so valuable often poses a threat to the privacy and security of users and companies, who are behind the digital location and trajectory data. Movement data can reveal the exact location of a user in real time to third parties, which is a violation of user privacy by per se. But it is not only the user location that is revealed by location traces; studying the movement patterns of a user can reveal sensitive information as the location of her home, where she works, religious preferences and even indicate health problems. Often, context information can help to reveal this details of users behavior. Therefore protecting context data is mandatory to forestall the leak of sensitive behavior information. To counter privacy and security risks, a series of technologies for protecting user privacy and security have been developed including data anonymization methods, protocols for securely posing location based queries and cryptographic methods for exchanging location information in location based social networks. On a different front, the notion of context can also be encompassed into privacy and security mechanisms to make the protection systems responsive to changing situations. For example, the amount of pri- vacy offered by privacy-enhancing techniques can change dynamically based on exogenous conditions; similarly security policies can be temporarily suspended and replaced when an emergency event occurs.
PriSMO is a workshop in conjunction with the 14th IEEE International Conference on Mobile Data Management (MDM 2013), Milan, Italy.
The purpose of this workshop is to encourage principled research that will lead to the advancement of the science of privacy and security on spatio-temporal data and in the study of the relation- ship between data protection and context, where context can be any kind of information characterizing a situation in a mobile computing setting.
Topics
Topics of interest to the workshop include, but are not limited to, the following:
? Privacy-preserving analysis/mining of movement and location data
? Privacy-preserving publishing of movement and location data
? Anonymity in location-based services
? Information hiding in geospatial data
? Interdisciplinary approaches and studies for location data(e.g., law, economy, sociology, etc. )
? Privacy policies in location based social networks
? Secure and private protocols for exchanging location information
? Systems for anonymous provision of location based services
? Security and privacy metrics for location data and location based services
? Utility and quality metrics for anonymized spatial data
? Quality of service metrics for anonymous location-based services
? Surveys of attacks against location based data, services and social networks
? Experience papers from real-world privacy solutions for movement data
? Context modeling in relation to privacy and security in mobile applications
? Context-dependent privacy in LBS
? Privacy of contexts streams
? Context-dependent privacy in data collection
? Context-dependent privacy in social networks
? Context-dependent access control policies
? Presence-based access control
? Privacy personalization based on context
? Context-related application requirements
? Case studies/real world applications of context-aware privacy and security