Maria Luisa Damiani
University of Milan
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Featured researches published by Maria Luisa Damiani.
data and knowledge engineering | 2008
Stefano Spaccapietra; Christine Parent; Maria Luisa Damiani; José Antônio Fernandes de Macêdo; Fábio Porto; Christelle Vangenot
Analysis of trajectory data is the key to a growing number of applications aiming at global understanding and management of complex phenomena that involve moving objects (e.g. worldwide courier distribution, city traffic management, bird migration monitoring). Current DBMS support for such data is limited to the ability to store and query raw movement (i.e. the spatio-temporal position of an object). This paper explores how conceptual modeling could provide applications with direct support of trajectories (i.e. movement data that is structured into countable semantic units) as a first class concept. A specific concern is to allow enriching trajectories with semantic annotations allowing users to attach semantic data to specific parts of the trajectory. Building on a preliminary requirement analysis and an application example, the paper proposes two modeling approaches, one based on a design pattern, the other based on dedicated data types, and illustrates their differences in terms of implementation in an extended-relational context.
symposium on access control models and technologies | 2005
Elisa Bertino; Barbara Catania; Maria Luisa Damiani; Paolo Perlasca
Securing access to data in location-based services and mobile applications requires the definition of spatially aware access control systems. Even if some approaches have already been proposed either in the context of geographic database systems or context-aware applications, a comprehensive framework, general and flexible enough to cope with spatial aspects in real mobile applications, is still missing. In this paper, we make one step towards this direction and we present GEO-RBAC, an extension of the RBAC model to deal with spatial and location-based information. In GEO-RBAC, spatial entities are used to model objects, user positions, and geographically bounded roles. Roles are activated based on the position of the user. Besides a physical position, obtained from a given mobile terminal or a cellular phone, users are also assigned a logical and device independent position, representing the feature (the road, the town, the region) in which they are located. To make the model more flexible and re-usable, we also introduce the concept of role schema, specifying the name of the role as well as the type of the role spatial boundary and the granularity of the logical position. We then extend GEO-RBAC to cope with hierarchies, modeling permission, user, and activation inheritance.
ACM Computing Surveys | 2013
Christine Parent; Stefano Spaccapietra; Chiara Renso; Gennady L. Andrienko; Natalia V. Andrienko; Vania Bogorny; Maria Luisa Damiani; Aris Gkoulalas-Divanis; José Antônio Fernandes de Macêdo; Nikos Pelekis; Yannis Theodoridis; Zhixian Yan
Focus on movement data has increased as a consequence of the larger availability of such data due to current GPS, GSM, RFID, and sensors techniques. In parallel, interest in movement has shifted from raw movement data analysis to more application-oriented ways of analyzing segments of movement suitable for the specific purposes of the application. This trend has promoted semantically rich trajectories, rather than raw movement, as the core object of interest in mobility studies. This survey provides the definitions of the basic concepts about mobility data, an analysis of the issues in mobility data management, and a survey of the approaches and techniques for: (i) constructing trajectories from movement tracks, (ii) enriching trajectories with semantic information to enable the desired interpretations of movements, and (iii) using data mining to analyze semantic trajectories and extract knowledge about their characteristics, in particular the behavioral patterns of the moving objects. Last but not least, the article surveys the new privacy issues that arise due to the semantic aspects of trajectories.
advances in geographic information systems | 2009
Gabriel Ghinita; Maria Luisa Damiani; Claudio Silvestri; Elisa Bertino
Mobile devices with positioning capabilities allow users to participate in novel and exciting location-based applications. For instance, users may track the whereabouts of their acquaintances in location-aware social networking applications, e.g., GoogleLatitude. Furthermore, users can request information about landmarks in their proximity. Such scenarios require users to report their coordinates to other parties, which may not be fully trusted. Reporting precise locations may result in serious privacy violations, such as disclosure of lifestyle details, sexual orientation, etc. A typical approach to preserve location privacy is to generate a cloaking region (CR) that encloses the user position. However, if locations are continuously reported, an attacker can correlate CRs from multiple timestamps to accurately pinpoint the user position within a CR. In this work, we protect against linkage attacks that infer exact locations based on prior knowledge about maximum user velocity. Assume user u who reports two consecutive cloaked regions A and B. We consider two distinct protection scenarios: in the first case, the attacker does not have information about the sensitive locations on the map, and the objective is to ensure that u can reach some point in B from any point in A. In the second case, the attacker knows the placement of sensitive locations, and the objective is to ensure that u can reach any point in B from any point in A. We propose spatial and temporal cloaking transformations to preserve user privacy, and we show experimentally that privacy can be achieved without significant quality of service deterioration.
IEEE Pervasive Computing | 2011
Maria Luisa Damiani; Claudio Silvestri; Elisa Bertino
Geosocial networking applications magnify the concern for location privacy because a users position can be disclosed to diverse untrusted parties. The Privacy Preserving Obfuscation Environment (Probe) framework supports semantic-location cloaking to protect this information.
International Journal of Geographical Information Science | 2004
Alberto Belussi; Elisa Bertino; Barbara Catania; Maria Luisa Damiani; Andrea Nucita
Access control is an important component of any database management system. Several access control models have been proposed for conventional databases. However, these models do not seem adequate for geographical databases, due to the peculiarities of geographical data. Previous work on access control models for geographical data mainly concerns raster maps (images). In this paper, we present a discretionary access control model for geographical maps. We assume that each map is composed of a set of features. Each feature is represented in one or more maps by spatial objects, described by means of different spatial properties: geometric properties, describing the shape, extension and location of the objects, and topological properties, describing the topological relationships existing among objects. The proposed access control model allows the security administrator to define authorizations against map objects at a very fine granularity level, taking into account the various spatial representations and the object dimension. The model also supports both positive and negative authorizations as well as different propagation rules that make access control very flexible.
mobile data management | 2012
Emre Yigitoglu; Maria Luisa Damiani; Osman Abul; Claudio Silvestri
This paper presents a privacy-preserving framework for the protection of sensitive positions in real time trajectories. We assume a scenario in which the sensitivity of users positions is space-varying, and so depends on the spatial context, while the users movement is confined to road networks and places. Typical users are the non-anonymous members of a geo-social network who agree to share their exact position whenever such position does not fall within a sensitive place, e.g. a hospital. Suspending location sharing while the user is inside a sensitive place is not an appropriate solution because the users stopovers can be easily inferred from the users trace. In this paper we present an extension of the semantic location cloaking model [1] originally developed for the cloaking of non-correlated positions in an unconstrained space. We investigate different algorithms for the generation of cloaked regions over the graph representing the urban setting. We also integrate methods to prevent velocity-based linkage attacks. Finally we evaluate experimentally the algorithms using a real data set.
advances in geographic information systems | 2009
Maria Luisa Damiani; Elisa Bertino; Claudio Silvestri
The widespread adoption of location-based services (LBS) raises increasing concerns for the protection of personal location information. A common strategy, referred to as obfuscation, to protect location privacy is based on forwarding the LSB provider a coarse user location instead of the actual user location. Conventional approaches, based on such technique, are however based only on geometric methods and therefore are unable to assure privacy when the adversary is aware of the geographical context. This paper provides a comprehensive solution to this problem. Our solution presents a novel approach that obfuscates the user location by taking into account the geographical context and users privacy preferences. We define several theoretical notions underlying our approach. We then propose a strategy for generating obfuscated spaces and an efficient algorithm which implements such a strategy. The paper includes several experimental results assessing performance, storage requirements and accuracy for the approach. The paper also discusses the system architecture and shows that the approach can be deployed also for clients running on small devices.
advances in geographic information systems | 2011
Michael S. Kirkpatrick; Maria Luisa Damiani; Elisa Bertino
As mobile computing devices are becoming increasingly dominant in enterprise and government organizations, the need for fine-grained access control in these environments continues to grow. Specifically, advanced forms of access control can be deployed to ensure authorized users can access sensitive resources only when in trusted locations. One technique that has been proposed is to augment role-based access control (RBAC) with spatial constraints. In such a system, an authorized user must be in a designated location in order to exercise the privileges associated with a role. In this work, we extend spatially aware RBAC systems by defining the notion of proximity-based RBAC. In our approach, access control decisions are not based solely on the requesting users location. Instead, we also consider the location of other users in the system. For instance, a policy in a government application could prevent access to a sensitive document if any civilians are present. We introduce our spatial model and the notion of proximity constraints. We define the syntax and semantics for the Prox-RBAC language, which can be used to specify these policy constraints. We introduce our enforcement architecture, including the protocols and algorithms for enforcing Prox-RBAC policies, and give a proof of functional correctness. Finally, we describe our work toward a Prox-RBAC prototype and present an informal security analysis.
international workshop on research issues in data engineering | 2004
Elisa Bertino; Maria Luisa Damiani; Davide Momini
In this paper, we present an access control model for spatial data on Web. Such a model is based on the following assumptions: first, spatial data consist of objects with sharp boundaries located in a geographical space; second, data are manipulated through the operations provided by a Web map management service. The goal of the system is to control the way data are accessed by users having different profiles. We propose an extension of classical models based on authorization rules by assigning authorizations a geographical scope. In such a way, the operations users may execute on spatial data may vary, depending on user identity and object position.