1. GEOPKDD - Meeting Venezia 17 Oct 051 Privacy-preserving data warehousing for spatio- temporal data Maria L. Damiani, Università Milano (I)

2. GEOPKDD - Meeting Venezia 17 Oct 052 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

3. GEOPKDD - Meeting Venezia 17 Oct 053 Content A reference architecture Spatial data warehousing: what is going on? Data security and privacy: a research direction

4. GEOPKDD - Meeting Venezia 17 Oct 054 A reference architecture APPLICATION SERVER LOCATION SERVER Network SPATIO-TEMPORAL DATA WAREHOUSE TermID Position …… Service Where is the closest bank? (X,Y)…DirServ bankAB12

5. GEOPKDD - Meeting Venezia 17 Oct 055 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

6. GEOPKDD - Meeting Venezia 17 Oct 056 The envisaged architecture APPLICATION SERVER Network Where is the closest bank? t (X',Y') PACS ( Privacy- pres Access Control System) SPATIAL DATA WAREHOUSE Position …… Service (X',Y') SPATIO-TEMPORAL DATA WAREHOUSE It controls who can do what and perturbs location data Pertubed data are stored

7. GEOPKDD - Meeting Venezia 17 Oct 057 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)

8. GEOPKDD - Meeting Venezia 17 Oct 058 Example ( from the previous meeting ) Time Cause #Victims Jan-03Speed2 Jan-03Speed1 Feb-04Weather1 Position Time Cause #Victims JanSpeed2 JanSpeed1 FebWeather1 Position

9. GEOPKDD - Meeting Venezia 17 Oct 059 S patial measure : hierarchy of spatial levels. A spatial level is an attribute whose values are OGC features. A Multigranular Spatial Schema S= where: D i 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, C SL is the set of tuples of the form: where: d i is a value for the dimension level DLv i ; m i is a value for the measure M i ; 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 A Multigranular Spatial Datawarehouse (MuSD)

10. GEOPKDD - Meeting Venezia 17 Oct 0510 Summary 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

11. GEOPKDD - Meeting Venezia 17 Oct 0511 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 APPLICATION SERVER Network Where is the closest bank? PACS ( Privacy- pres Access Control System)

12. GEOPKDD - Meeting Venezia 17 Oct 0512 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)

13. GEOPKDD - Meeting Venezia 17 Oct 0513 A scenario: a park Park ranger Surveyor Park tourist

14. GEOPKDD - Meeting Venezia 17 Oct 0514 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

15. GEOPKDD - Meeting Venezia 17 Oct 0515 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)

16. GEOPKDD - Meeting Venezia 17 Oct 0516 Conclusions Two sub-activities. –Spatial Data warehousing –PACS: privacy preserving access control model Any preference?