40 resultados para Privacy

em QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast


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The research examines the relationships between three common trust considerations (vendor, Internet and third parties) and attitudes towards online purchasing. The study incorporates privacy and security concerns as a moderating variable and finds that these relationships vary depending on the level of concerns a consumer has when purchasing online. The study suggests that "fears" surrounding the Internet as a place to do business still hinder the use of it for e-commerce purposes, but that the presence of a reputable agent might in some manner mitigate this risk. In the context of business to consumer relationships trust in the vendor is important for the consumer to accept any risk associated with a transaction. Theoretical implications for online customer behavior theory are also discussed. © 2009 Elsevier Inc.

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Privacy has now become a major topic not only in law but in computing, psychology, economics and social studies, and the explosion in scholarship has made it difficult for the student to traverse the field and identify the significant issues across the many disciplines. This series brings together a collection of significant papers with a multi-disciplinary approach which enable the reader to navigate through the complexities of the issues and make sense of the prolific scholarship published in this field.

The three volumes in this series address different themes: an anthropological approach to what privacy means in a cultural context; the issue of state surveillance where the state must both protect the individual and protect others from that individual and also protect itself; and, finally, what privacy might mean in a world where government and commerce collect data incessantly. The regulation of privacy is continually being called for and these papers help enable understanding of the ethical rationales behind the choices made in the sphere of regulation of privacy.

The articles presented in each of these collections have been chosen for the quality of their scholarship and their utility to the researcher, and feature a variety of approaches. The articles which debate the technical context of privacy are accessible to those from the arts and humanities; overall, the breadth of approach taken in the choice of articles has created a series which is an invaluable and important resource for lecturers, researchers and student.

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Autonomous agents may encapsulate their principals' personal data attributes. These attributes may be disclosed to other agents during agent interactions, producing a loss of privacy. Thus, agents need self-disclosure decision-making mechanisms to autonomously decide whether disclosing personal data attributes to other agents is acceptable or not. Current self-disclosure decision-making mechanisms consider the direct benefit and the privacy loss of disclosing an attribute. However, there are many situations in which the direct benefit of disclosing an attribute is a priori unknown. This is the case in human relationships, where the disclosure of personal data attributes plays a crucial role in their development. In this paper, we present self-disclosure decision-making mechanisms based on psychological findings regarding how humans disclose personal information in the building of their relationships. We experimentally demonstrate that, in most situations, agents following these decision-making mechanisms lose less privacy than agents that do not use them. (C) 2012 Elsevier Inc. All rights reserved.

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Privacy region protection in video surveillance systems is an active topic at present. In previous research, a binary mask mechanism has been developed to indicate the privacy region; however this incurs a significant bitrate overhead. In this paper, an adaptive binary mask is proposed to represent the privacy region. In a practical privacy region protection application, in which the privacy region typically occupies less than half of the overall frame and is rectangular or approximately rectangular, the proposed adaptive binary mask can effectively reduce the bitrate overhead. The proposed method can also be easily applied to the FMO mechanism of H.264/AVC, providing both error resilience and a lower bitrate overhead.

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The notion of privacy represents a central criterion for both indoor and outdoor social spaces in most traditional Arab settlements. This paper investigates privacy and everyday life as determinants of the physical properties of the built and urban fabric and will study their impact on traditional settlements and architecture of the home in the contemporary Iraqi city. It illustrates the relationship between socio-cultural aspects of public/private realms using the notion of the social sphere as an investigative tool of the concept of social space in Iraqi houses and local communities (Mahalla). This paper reports that in spite of the impact of other factors in articulating built forms, privacy embodies the primary role under the effects of Islamic rules, principles and culture. The crucial problem is the underestimation of traditional inherited values through opening social spaces to the outside that giving unlimited accesses to the indoor social environment creating many problems with regard to privacy and communal social integration.

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Biometric systems provide a valuable service in helping to identify individuals from their stored personal details. Unfortunately, with the rapidly increasing use of such systems, there is a growing concern about the possible misuse of that information. To counteract the threat, the European Union (EU) has introduced comprehensive legislation that seeks to regulate data collection and help strengthen an individual’s right to privacy. This article looks at the implications of the legislation for biometric system deployment. After an initial consideration of current privacy concerns, it examines what is meant by ‘personal data’ and its protection, in legislation terms. Also covered are issues around the storage of biometric data, including its accuracy, its security, and justification for what is collected. Finally, the privacy issues are illustrated through three biometric use cases: border security, online bank access control and customer profiling in stores.

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While video surveillance systems have become ubiquitous in our daily lives, they have introduced concerns over privacy invasion. Recent research to address these privacy issues includes a focus on privacy region protection, whereby existing video scrambling techniques are applied to specific regions of interest (ROI) in a video while the background is left unchanged. Most previous work in this area has only focussed on encrypting the sign bits of nonzero coefficients in the privacy region, which produces a relatively weak scrambling effect. In this paper, to enhance the scrambling effect for privacy protection, it is proposed to encrypt the intra prediction modes (IPM) in addition to the sign bits of nonzero coefficients (SNC) within the privacy region. A major issue with utilising encryption of IPM is that drift error is introduced outside the region of interest. Therefore, a re-encoding method, which is integrated with the encryption of IPM, is also proposed to remove drift error. Compared with a previous technique that uses encryption of IPM, the proposed re-encoding method offers savings in the bitrate overhead while completely removing the drift error. Experimental results and analysis based on H.264/AVC were carried out to verify the effectiveness of the proposed methods. In addition, a spiral binary mask mechanism is proposed that can reduce the bitrate overhead incurred by flagging the position of the privacy region. A definition of the syntax structure for the spiral binary mask is given. As a result of the proposed techniques, the privacy regions in a video sequence can be effectively protected by the enhanced scrambling effect with no drift error and a lower bitrate overhead.

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Although visual surveillance has emerged as an effective technolody for public security, privacy has become an issue of great concern in the transmission and distribution of surveillance videos. For example, personal facial images should not be browsed without permission. To cope with this issue, face image scrambling has emerged as a simple solution for privacyrelated applications. Consequently, online facial biometric verification needs to be carried out in the scrambled domain thus bringing a new challenge to face classification. In this paper, we investigate face verification issues in the scrambled domain and propose a novel scheme to handle this challenge. In our proposed method, to make feature extraction from scrambled face images robust, a biased random subspace sampling scheme is applied to construct fuzzy decision trees from randomly selected features, and fuzzy forest decision using fuzzy memberships is then obtained from combining all fuzzy tree decisions. In our experiment, we first estimated the optimal parameters for the construction of the random forest, and then applied the optimized model to the benchmark tests using three publically available face datasets. The experimental results validated that our proposed scheme can robustly cope with the challenging tests in the scrambled domain, and achieved an improved accuracy over all tests, making our method a promising candidate for the emerging privacy-related facial biometric applications.