Spiros Skiadopoulos

PRIVE: anonymous location-based queries in distributed mobile systems

Nowadays, mobile users with global positioning devices canaccess Location Based Services (LBS) and query about pointsof interest in their proximity. For such applications to succeed,privacy and confidentiality are essential. Encryptionalone is not adequate; although it safeguards the systemagainst eavesdroppers, the queries themselves may disclosethe location and identity of the user. Recently, there havebeen proposed centralized architectures based on K-anonymity,which utilize an intermediate anonymizer between themobile users and the LBS. However, the anonymizer mustbe updated continuously with the current locations of allusers. Moreover, the complete knowledge of the entire systemposes a security threat, if the anonymizer is compromised.In this paper we address two issues: (i) We show thatexisting approaches may fail to provide spatial anonymityfor some distributions of user locations and describe a noveltechnique which solves this problem. (ii) We propose Prive,a decentralized architecture for preserving the anonymityof users issuing spatial queries to LBS. Mobile users self-organizeinto an overlay network with good fault toleranceand load balancing properties. Prive avoids the bottleneckcaused by centralized techniques both in terms of anonymizationand location updates. Moreover, the system state isdistributed in numerous users, rendering Prive resilient toattacks. Extensive experimental studies suggest that Priveis applicable to real-life scenarios with large populations ofmobile users.

Composing cardinal direction relations

We study the recent proposal of Goyal and Egenhofer who presented a model for qualitative spatial reasoning about cardinal directions. Our approach is formal and complements the presentation of Goyal and Egerdaofer. We focus our efforts on the composition operator for two cardinal direction relations. We consider two interpretations of the composition operator: consistency-based and existential composition. We point out that the only published method to compute the consistency-based composition does not always work correctly. Then, we consider progressively more expressive classes of cardinal direction relations and give consistency-based composition algorithms for these classes. Our theoretical framework allows us to prove formally that our algorithms are correct. When we consider existential composition, we demonstrate that the binary relation resulting from the composition of two cardinal direction relations cannot be expressed using the relations defined by Goyal and Egenhofer. Finally, we discuss some extensions to the basic model and consider the composition problem for these extensions.

A generic and customizable framework for the design of ETL scenarios

Extraction-transformation-loading (ETL) tools are pieces of software responsible for the extraction of data from several sources, their cleansing, customization and insertion into a data warehouse. In this paper, we delve into the logical design of ETL scenarios and provide a generic and customizable framework in order to support the DW designer in his task. First, we present a metamodel particularly customized for the definition of ETL activities. We follow a workflow-like approach, where the output of a certain activity can either be stored persistently or passed to a subsequent activity. Also, we employ a declarative database programming language, LDL, to define the semantics of each activity. The metamodel is generic enough to capture any possible ETL activity. Nevertheless, in the pursuit of higher reusability and flexibility, we specialize the set of our generic metamodel constructs with a palette of frequently used ETL activities, which we call templates. Moreover, in order to achieve a uniform extensibility mechanism for this library of built-ins, we have to deal with specific language issues. Therefore, we also discuss the mechanics of template instantiation to concrete activities. The design concepts that we introduce have been implemented in a tool, ARKTOS II, which is also presented.

MOBIHIDE: a mobilea peer-to-peer system for anonymous location-based queries

Modern mobile phones and PDAs are equipped with positioning capabilities (e.g., GPS). Users can access public location-based services (e.g., Google Maps) and ask spatial queries. Although communication is encrypted, privacy and confidentiality remain major concerns, since the queries may disclose the location and identity of the user. Commonly, spatial K-anonymity is employed to hide the query initiator among a group of K users. However, existing work either fails to guarantee privacy, or exhibits unacceptably long response time. In this paper we propose MobiHide, a Peer-to-Peer system for anonymous location-based queries, which addresses these problems. MobiHide employs the Hilbert space-filling curve to map the 2-D locations of mobile users to 1-D space. The transformed locations are indexed by a Chord-based distributed hash table, which is formed by the mobile devices. The resulting Peer-to-Peer system is used to anonymize a query by mapping it to a random group of K users that are consecutive in the 1-D space. Compared to existing state-of-the-art, MobiHide does not provide theoretical anonymity guarantees for skewed query distributions. Nevertheless, it achieves strong anonymity in practice, and it eliminates system hotspots. Our experimental evaluation shows that MobiHide has good load balancing and fault tolerance properties, and is applicable to real-life scenarios with numerous mobile users.

Supporting Streaming Updates in an Active Data Warehouse

Active data warehousing has emerged as an alternative to conventional warehousing practices in order to meet the high demand of applications for up-to-date information. In a nutshell, an active warehouse is refreshed on-line and thus achieves a higher consistency between the stored information and the latest data updates. The need for on-line warehouse refreshment introduces several challenges in the implementation of data warehouse transformations, with respect to their execution time and their overhead to the warehouse processes. In this paper, we focus on a frequently encountered operation in this context, namely, the join of a fast stream S of source updates with a disk-based relation R, under the constraint of limited memory. This operation lies at the core of several common transformations, such as, surrogate key assignment, duplicate detection or identification of newly inserted tuples. We propose a specialized join algorithm, termed mesh join (MeshJoin), that compensates for the difference in the access cost of the two join inputs by (a) relying entirely on fast sequential scans of R, and (b) sharing the I/O cost of accessing R across multiple tuples of S. We detail the Mesh Join algorithm and develop a systematic cost model that enables the tuning of Mesh Join for two objectives: maximizing throughput under a specific memory budget or minimizing memory consumption for a specific throughput. We present an experimental study that validates the performance of Mesh Join on synthetic and real-life data. Our results verify the scalability of Mesh-Join to fast streams and large relations, and demonstrate its numerous advantages over existing join algorithms.

Arktos: towards the modeling, design, control and execution of ETL processes

Extraction-Transformation-loading (ETL) tools are pieces of software responsible for the extraction of data from several sources, their cleansing, customization and insertion into a data warehouse. Literature and personal experience have guided us to conclude that the problems concerning the ETL tools are primarily problems of complexity, usability and price. To deal with these problems we provide a uniform metamodel for ETL processes, covering the aspects of data warehouse architecture, activity modeling, contingency treatment and quality management. The ETL tool we have developed, namely Arktos, is capable of modeling and executing practical ETL scenarios by providing explicit primitives for the capturing of common tasks. Arktos provides three ways to describe an ETL scenario: a graphical point-and-click front end and two declarative languages: XADL (an XML variant), which is more verbose and easy to read and SADL (an SQL-like language) which has a quite compact syntaxand is, thus, easier for authoring. r 2001 Elsevier Science Ltd. All rights reserved.

GraMi: frequent subgraph and pattern mining in a single large graph

Mining frequent subgraphs is an important operation on graphs; it is defined as finding all subgraphs that appear frequently in a database according to a given frequency threshold. Most existing work assumes a database of many small graphs, but modern applications, such as social networks, citation graphs, or protein-protein interactions in bioinformatics, are modeled as a single large graph. In this paper we present GraMi, a novel framework for frequent subgraph mining in a single large graph. GraMi undertakes a novel approach that only finds the minimal set of instances to satisfy the frequency threshold and avoids the costly enumeration of all instances required by previous approaches. We accompany our approach with a heuristic and optimizations that significantly improve performance. Additionally, we present an extension of GraMi that mines frequent patterns. Compared to subgraphs, patterns offer a more powerful version of matching that captures transitive interactions between graph nodes (like friend of a friend) which are very common in modern applications. Finally, we present CGraMi, a version supporting structural and semantic constraints, and AGraMi, an approximate version producing results with no false positives. Our experiments on real data demonstrate that our framework is up to 2 orders of magnitude faster and discovers more interesting patterns than existing approaches.

On the consistency of cardinal direction constraints

We present a formal model for qualitative spatial reasoning with cardinal directions utilizing a co-ordinate system. Then, we study the problem of checking the consistency of a set of cardinal direction constraints. We introduce the first algorithm for this problem, prove its correctness and analyze its computational complexity. Utilizing the above algorithm, we prove that the consistency checking of a set of basic (i.e., non-disjunctive) cardinal direction constraints can be performed in O(n^5) time. We also show that the consistency checking of a set of unrestricted (i.e., disjunctive and non-disjunctive) cardinal direction constraints is NP-complete. Finally, we briefly discuss an extension to the basic model and outline an algorithm for the consistency checking problem of this extension.

Advanced visualization for OLAP

Data visualization is one of the big issues of database research. OLAP as a decision support technology is highly related to the developments of data visualization area. In this paper we demonstrate how the Cube Presentation Model (CPM), a novel presentational model for OLAP screens, can be naturally mapped on the Table Lens, which is an advanced visualization technique from the Human-Computer Interaction area, particularly tailored for cross-tab reports. We consider how the user interacts with an OLAP screen and based on the particularities of Table Lens, we propose an automated proactive users support. Finally, we discuss the necessity and the applicability of advanced visualization techniques in the presence of recent technological developments.

Composing Cardinal Direction Relations

We study the recent proposal of Goyal and Egenhofer who presented a model for qualitative spatial reasoning about cardinal directions. Our approach is formal and complements the presentation of Goyal and Egenhofer. We focus our efforts on the operation of composition for two cardinal direction relations. We point out that the only published method to compute the composition does not always work correctly. Then we consider progressively more expressive classes of cardinal direction relations and give composition algorithms for these classes. Our theoretical framework allows us to prove formally that our algorithms are correct. Finally, we demonstrate that in some cases, the binary relation resulting from the composition of two cardinal direction relations cannot be expressed using the relations defined by Goyal and Egenhofer.