Approximate and exact hybrid algorithms for private nearest-neighbor queries with database protection

Mobile devices with global positioning capabilities allow users to retrieve points of interest (POI) in their proximity. To protect user privacy, it is important not to disclose exact user coordinates to un-trusted entities that provide location-based services. Currently, there are two main approaches to protect the location privacy of users: (i) hiding locations inside cloaking regions (CRs) and (ii) encrypting location data using private information retrieval (PIR) protocols. Previous work focused on finding good trade-offs between privacy and performance of user protection techniques, but disregarded the important issue of protecting the POI dataset D. For instance, location cloaking requires large-sized CRs, leading to excessive disclosure of POIs (O(|D|) in the worst case). PIR, on the other hand, reduces this bound to \(O(\sqrt{|D|})\), but at the expense of high processing and communication overhead. We propose hybrid, two-step approaches for private location-based queries which provide protection for both the users and the database. In the first step, user locations are generalized to coarse-grained CRs which provide strong privacy. Next, a PIR protocol is applied with respect to the obtained query CR. To protect against excessive disclosure of POI locations, we devise two cryptographic protocols that privately evaluate whether a point is enclosed inside a rectangular region or a convex polygon. We also introduce algorithms to efficiently support PIR on dynamic POI sub-sets. We provide solutions for both approximate and exact NN queries. In the approximate case, our method discloses O(1) POI, orders of magnitude fewer than CR- or PIR-based techniques. For the exact case, we obtain optimal disclosure of a single POI, although with slightly higher computational overhead. Experimental results show that the hybrid approaches are scalable in practice, and outperform the pure-PIR approach in terms of computational and communication overhead.     

EXAM: a comprehensive environment for the analysis of access control policies

Policy integration and inter-operation is often a crucial requirement when parties with different access control policies need to participate in collaborative applications and coalitions. Such requirement is even more difficult to address for dynamic large-scale collaborations, in which the number of access control policies to analyze and compare can be quite large. An important step in policy integration and inter-operation is to analyze the similarity of policies. Policy similarity can sometimes also be a pre-condition for establishing a collaboration, in that a party may enter a collaboration with another party only if the policies enforced by the other party match or are very close to its own policies. Existing approaches to the problem of analyzing and comparing access control policies are very limited, in that they only deal with some special cases. By recognizing that a suitable approach to the policy analysis and comparison requires combining different approaches, we propose in this paper a comprehensive environment—EXAM. The environment supports various types of analysis query, which we categorize in the paper. A key component of such environment, on which we focus in the paper, is the policy analyzer able to perform several types of analysis. Specifically, our policy analyzer combines the advantages of existing MTBDD-based and SAT-solver-based techniques. Our experimental results, also reported in the paper, demonstrate the efficiency of our analyzer.     

A conditional purpose-based access control model with dynamic roles

This paper presents a model for privacy preserving access control which is based on variety of purposes. Conditional purpose is applied along with allowed purpose and prohibited purpose in the model. It allows users using some data for certain purpose with conditions. The structure of conditional purpose-based access control model is defined and investigated through dynamic roles. Access purpose is verified in a dynamic behavior, based on subject attributes, context attributes and authorization policies. Intended purposes are dynamically associated with the requested data object during the access decision. An algorithm is developed to achieve the compliance computation between access purposes and intended purposes and is illustrated with Role-based access control (RBAC) in a dynamic manner to support conditional purpose-based access control. According to this model, more information from data providers can be extracted while at the same time assuring privacy that maximizes the usability of consumers’ data. It extends traditional access control models to a further coverage of privacy preserving in data mining atmosphere. The structure helps enterprises to circulate clear privacy promise, to collect and manage user preferences and consent.     

A distributed approach to enabling privacy-preserving model-based classifier training

This paper proposes a novel approach for privacy-preserving distributed model-based classifier training. Our approach is an important step towards supporting customizable privacy modeling and protection. It consists of three major steps. First, each data site independently learns a weak concept model (i.e., local classifier) for a given data pattern or concept by using its own training samples. An adaptive EM algorithm is proposed to select the model structure and estimate the model parameters simultaneously. The second step deals with combined classifier training by integrating the weak concept models that are shared from multiple data sites. To reduce the data transmission costs and the potential privacy breaches, only the weak concept models are sent to the central site and synthetic samples are directly generated from these shared weak concept models at the central site. Both the shared weak concept models and the synthetic samples are then incorporated to learn a reliable and complete global concept model. A computational approach is developed to automatically achieve a good trade off between the privacy disclosure risk, the sharing benefit and the data utility. The third step deals with validating the combined classifier by distributing the global concept model to all these data sites in the collaboration network while at the same time limiting the potential privacy breaches. Our approach has been validated through extensive experiments carried out on four UCI machine learning data sets and two image data sets.

Impact assessment of odours emitted by a wastewater treatment plant

Complaints from the Domingos Martins population about sewage odours in the city made the district attorney order an impact assessment of the odours emitted by the city wastewater treatment plant (WWTP). This study comprised various techniques, models and population surveys. In 2007, an odour emission model proved that the main hydrogen sulphide emitter was the aeration tank of the WWTP (13.5 g h(-1)) and such emissions, according to CALPUFF model, should be perceived in the whole Domingos Martins city centre area. In this area, 58% of those interviewed were annoyed by the WWTP odours. However, in 2009, the odour monitoring panel recorded few odour occurrences. A second population survey showed that hereafter only 20% of those interviewed were annoyed by the WWTP emissions. Odour emission and dispersion models run with 2010 data proved a drastic reduction of the WWTP aeration tank emissions and consequently the city centre was not bothered by WWTP emissions anymore. The odour emission reduction was due to the modification of the WWTP aeration tank system. Despite the odour emission reduction, houses located southeast of the WWTP were still annoyed by sewage odours. However, in this part of the town, other sources of sewage odours have been found.     

Bringing Scheme programming to the iPhone—Experience

The iPhone SDK provides a powerful platform for the development of applications that make use of iPhone capabilities, such as sensors, GPS, Wi‐Fi, or Bluetooth connectivity. We observe that so far the development of iPhone applications has mostly been restricted to using Objective‐C. However, developing applications in plain Objective‐C on the iPhone OS suffers from limitations, such as the need for explicit memory management and lack of syntactic extension mechanism. Moreover, when developing distributed applications in Objective‐C, programmers have to manually deal with distribution concerns, such as service discovery, remote communication, and failure handling. In this paper, we discuss our experience in porting the Scheme programming language to the iPhone OS and how it can be used together with Objective‐C to develop iPhone applications. To support the interaction between Scheme programs and the underlying iPhone APIs, we have implemented a language symbiosis layer that enables programmers to access the iPhone SDK libraries from Scheme. In addition, we have designed high‐level distribution constructs to ease the development of distributed iPhone applications in an event‐driven style. We validate and discuss these constructs with a series of examples, including an iPod controller, a maps application, and a distributed multiplayer Scrabble‐like game. We discuss the lessons learned from this experience for other programming language ports to mobile platforms. Copyright © 2011 John Wiley & Sons, Ltd.     

Predictors of Resilience in Maltreated and Nonmaltreated Latino Children.

To date, few studies have sought to investigate the effects of child maltreatment and processes influencing maladaptation and resilience in Latino children. In the current investigation, multiple aspects of functioning, personal resources, and relationship features were examined in school-age maltreated and nonmaltreated Latino children. Maltreated Latino children were found to have fewer areas of resilient functioning. Ego-resiliency and ego-control, as personal resources, and the ability to form a positive relationship with an adult figure outside of the immediate family predicted resilience. However, certain aspects of interpersonal functioning were differentially related to resilience for maltreated and nonmaltreated Latino children. These findings have implications for understanding how resilience can be promoted in maltreated and nonmaltreated Latino children. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Structural and Magnetic Properties of the New La2SrCo2FeO9 Triple Perovskite

In this work, we report synthesis and characterization of the new La₂SrCo₂FeO₉ triple perovskite material. The samples were produced by the solid-state reaction method. The analyses of the XRD patterns were made by Rietveld refinement through the GSAS code. The results reveal that the material crystallizes in an orthorhombic complex perovskite, space group Immm (#71) with lattice parameters a=5.4314(3) ?, b=5.4583(3) ? and c=7.7018(2) ?. SEM micrographs evidence a strongly diffused granular morphology with mean grain size of 2 μm and the EDX spectra show that the chemical composition of samples are in good agreement with the nominal values of the stoichiometric formula. ⁵⁷Fe Mössbauer spectroscopy recorded at 300 K reveals two sites in concordance with the X-ray diffraction measurements, and its valence state is +3, as determined from the isomer shift found. At 4.2 K magnetic ordering with canting of the Fe moments is found. Measurements of the magnetization as a function of temperature permitted us to determine the ferromagnetic characteristic of material with an effective magnetic moment of 9.7μ _B.