Privacy-preserving data warehousing for spatio-temporal data

1. Privacy-preserving data warehousing for spatio-temporal data Maria L. Damiani, Università Milano (I) GEOPKDD - Meeting Venezia 17 Oct 05

2. Report • The report contains two contributions: • M.L. Damiani, S. Spaccapietra, Spatial Data Warehouse Modelling • M.L. Damiani, E. Bertino, Data Security and Privacy in Location-Aware Applications: a Research Direction GEOPKDD - Meeting Venezia 17 Oct 05

3. TermID Position …… Service A reference architecture Where is the closest bank? SPATIO-TEMPORAL DATA WAREHOUSE APPLICATION SERVER AB12 (X,Y) … DirServ bank Network LOCATION SERVER GEOPKDD - Meeting Venezia 17 Oct 05

4. Location privacy concerns • Location privacy: the ability to prevent other parties from learning one's current or past location. A threat to location privacy thus occurs when an adversary can obtain an individual’s location information and can identify the individual. • Approaches to location privacy include: • Policy-based: personal data are recorded and a privacy policy defines how data can be disclosed • Location data perturbation: location data are modified before data are recorded GEOPKDD - Meeting Venezia 17 Oct 05

5. SPATIAL DATA WAREHOUSE Position …… Service The envisaged architecture Where is the closest bank? SPATIO-TEMPORAL DATA WAREHOUSE PACS (Privacy- pres Access Control System) APPLICATION SERVER t (X',Y') (X',Y') Network It controls who can do what and perturbs location data Pertubed data are stored GEOPKDD - Meeting Venezia 17 Oct 05

6. Topic: Spatial data warehouse modelling • Focus on multidimensional data models for spatial data • Spatial + {fact, dimensions hierarchies, measures, OLAP} • Motivations • It provides a framework for the representation and aggregation of spatial data at different levels of granularity • Front end for the user • However, a comprehensive and formal model is still an open issue • Two main contributions of the report: • A picture of the research area • A model with spatial measures at multiple levels of geometric granularity (MuSD) GEOPKDD - Meeting Venezia 17 Oct 05

7. Time Cause #Victims Jan-03 Speed 2 Jan-03 Speed 1 Feb-04 Weather 1 Position Example (from the previous meeting) Time Cause #Victims Jan Speed 2 Jan Speed 1 Feb Weather 1 Position GEOPKDD - Meeting Venezia 17 Oct 05

8. A Multigranular Spatial Datawarehouse (MuSD) • Spatial measure: hierarchy of spatial levels. A spatial level is an attribute whose values are OGC features. • A Multigranular Spatial Schema S= <D1, ..Dn, M1, ...Mm, SM>where: Di is a dimension, for each i =1, .., n  Mj is a non-spatial measure, for each j =1, .., m SM is a spatial measure • Given a schema level SL, a cube for SL, CSL is the set of tuples of the form: <d1, ..., dn, m1, ..., mm, sv> where: di is a value for the dimension level DLvi; mi is a value for the measure Mi; sv is the value for the spatial measure level Slv • Issues: • Functional dependencies between the levels of the spatial measure and spatial dimensions • Dynamic coarsening of spatial measures • Spatial Olap GEOPKDD - Meeting Venezia 17 Oct 05

9. A framework has been proposed based on the notion of multigranular spatial schema and cube and spatial OLAP Further the proposed framework has been formally defined However the framework is still general and a number of issues are open. Moreover spatio-temporal data are not taken into account yet Pubblication: M.L. Damiani and S. Spaccapietra. Spatial Data Warehouse Modelling. Chapter of the book: Processing and Managing Complex Data for Decision Support, IDEA Grout Inc., to appear Summary GEOPKDD - Meeting Venezia 17 Oct 05

10. Topic: data security and privacy for location-aware applications • The idea is to base the development of PACS on GEO-RBAC an access control model proposed for the mobile setting (ACM Sacmat 05) • Motivations: • The model has a number of characteristics which are useful for location privacy purposes • It provides a framework that enables location data perturbation • Policies can be specified accounting of user preferences Where is the closest bank? PACS (Privacy- pres Access Control System) APPLICATION SERVER Network GEOPKDD - Meeting Venezia 17 Oct 05

11. GEO-RBAC: a quick overview • It is an access control model for mobile organizations • An access control model is a model which describes who can do what on which resource • By mobile organization we mean a community of individuals that, because of the role they have, need to access common information resources through LBS ( e.g. enterprise operating on field, health and leisure organization, civil and military coalitions) GEOPKDD - Meeting Venezia 17 Oct 05

12. Park tourist Park ranger Surveyor A scenario: a park GEOPKDD - Meeting Venezia 17 Oct 05

13. User are characterized by roles The roles of users may have a spatial boundary (spatial roles) Since the user is a moving user the roles may vary with the position Thus depending on the position different LBS are available GEOPKDD - Meeting Venezia 17 Oct 05

14. Major features • The position model • Real position Vs Logical position to abstract from the positioning technology • Real position: geometry • Logical position: "semantic location": building, road etc.. • Location mapping function to "perturb" location data • Example: maps a GPS point onto the closest road segment • The spatial role model • Spatial role : describes a user through a spatially bounded functional role • Example: the role extent of the park tourist is the park • Role schema vs role instance. The role schema describes the location perturbation technique to be applied to the instance of the role A schema: Tourist ( Park, Road, mapToRoad ) An instance: Tourist (Yellowstone) GEOPKDD - Meeting Venezia 17 Oct 05

15. Conclusions • Two sub-activities. • Spatial Data warehousing • PACS: privacy preserving access control model • Any preference? GEOPKDD - Meeting Venezia 17 Oct 05