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Abbadi, Imad Mahmoud Aref - One of the best experts on this subject based on the ideXlab platform.
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Digital Rights Management for Personal Networks
2008Co-Authors: Abbadi, Imad Mahmoud ArefAbstract:The thesis is concerned with Digital Rights Management (DRM), and in particular with DRM for networks of devices owned by a single individual. This thesis focuses on the problem of preventing illegal copying of digital assets without jeopardising the right of legitimate licence holders to transfer content between their own devices, which collectively make up what we refer to as an authorised Domain. An ideal list of DRM requirements is specified, which takes into account the points of view of users, content providers and copyright law. An approach is then developed for assessing DRM systems based on the defined DRM requirements; the most widely discussed DRM schemes are then analysed and assessed, where the main focus is on schemes which address the concept of an authorised Domain. Based on this analysis we isolate the issues underlying the content piracy problem, and then provide a generic framework for a DRM system addressing the identified content piracy issues. The defined generic framework has been designed to avoid the weaknesses found in other schemes. The main contributions of this thesis include developing four new approaches that can be used to implement the proposed generic framework for managing an authorised Domain. The four novel solutions all involve secure means for creating, managing and using a secure Domain, which consists of all devices owned by a single owner. The schemes allow secure content sharing between devices in a Domain, and prevent the illegal copying of content to devices outside the Domain. In addition, each solution incorporates a method for binding a Domain to a single owner, ensuring that only a single consumer owns and manages a Domain. This enables binding of content licences to a single owner, thereby limiting illicit content proliferation. In the first solution, Domain owners are authenticated using two-factor authentication, which involves "something the Domain owner has", i.e. a master control device that controls and manages consumers Domains, and binds devices joining a Domain to itself, and "something the Domain owner is or knows", i.e. a biometric or password/PIN authentication mechanism that is implemented by the master control device. In the second solution, Domain owners are authenticated using their payment cards, building on existing electronic payment systems by ensuring that the name and the date of birth of a Domain creator are the same for all devices joining a Domain. In addition, this solution helps to protect consumers' privacy; unlike in existing electronic payment systems, payment card details are not exposed to third parties. The third solution involves the use of a Domain-specific mobile phone and the mobile phone network operator to authenticate a Domain owner before devices can join a Domain. The fourth solution involves the use of location-based services, ensuring that devices joining a consumer Domain are located in physical proximity to the addresses registered for this Domain. This restricts Domain Membership to devices in predefined geographical locations, helping to ensure that a single consumer owns and manages each Domain
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Digital Rights Management for Personal Networks
2008Co-Authors: Abbadi, Imad Mahmoud ArefAbstract:The thesis is concerned with Digital Rights Management (DRM), and in particular with DRM for networks of devices owned by a single individual. This thesis focuses on the problem of preventing illegal copying of digital assets without jeopardising the right of legitimate licence holders to transfer content between their own devices, which collectively make up what we refer to as an authorised Domain. An ideal list of DRM requirements is specified, which takes into account the points of view of users, content providers and copyright law. An approach is then developed for assessing DRM systems based on the defined DRM requirements; the most widely discussed DRM schemes are then analysed and assessed, where the main focus is on schemes which address the concept of an authorised Domain. Based on this analysis we isolate the issues underlying the content piracy problem, and then provide a generic framework for a DRM system addressing the identified content piracy issues. The defined generic framework has been designed to avoid the weaknesses found in other schemes. The main contributions of this thesis include developing four new approaches that can be used to implement the proposed generic framework for managing an authorised Domain. The four novel solutions all involve secure means for creating, managing and using a secure Domain, which consists of all devices owned by a single owner. The schemes allow secure content sharing between devices in a Domain, and prevent the illegal copying of content to devices outside the Domain. In addition, each solution incorporates a method for binding a Domain to a single owner, ensuring that only a single consumer owns and manages a Domain. This enables binding of content licences to a single owner, thereby limiting illicit content proliferation. In the first solution, Domain owners are authenticated using two-factor authentication, which involves 'something the Domain owner has', Le. a master control device that controls and manages consumers Domains, and binds devices joining a Domain to itself, and 'something the Domain owner is or knows', i.e. a biometric or password/PIN authentication mechanism that is implemented by the master control device. In the second solution, Domain owners are authenticated using their payment cards, building on existing electronic payment systems by ensuring that the name and the date of birth of a Domain creator are the same for all devices joining a Domain. In addition, this solution helps to protect consumers' privacy; unlike in existing electronic payment systems, payment card details are not exposed to third parties. The third solution involves the use of a Domain-specific mobile phone and the mobil~ phone network operator to authenticate a Domain owner before devices can join a Domain. The fourth solution involves the use of location-based services, ensuring that devices joining a consumer Domain are located in physical proximity to the addresses registered for this Domain. This restricts Domain Membership to devices in predefined geographical locations, helping to ensure that a single consumer owns and manages each Domain.EThOS - Electronic Theses Online ServiceGBUnited Kingdo
Shanae M Burns - One of the best experts on this subject based on the ideXlab platform.
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research data sharing in the australian national science agency understanding the relative importance of organisational disciplinary and Domain specific influences
PLOS ONE, 2020Co-Authors: Claire Mason, Paul Box, Shanae M BurnsAbstract:This study delineates the relative importance of organisational, research discipline and application Domain factors in influencing researchers' data sharing practices in Australia's national scientific and industrial research agency. We surveyed 354 researchers and found that the number of data deposits made by researchers were related to the openness of the data culture and the contractual inhibitors experienced by researchers. Multi-level modelling revealed that organisational unit Membership explained 10%, disciplinary Membership explained 6%, and Domain Membership explained 4% of the variance in researchers' intentions to share research data. However, only the organisational measure of openness to data sharing explained significant unique variance in data sharing. Thus, whereas previous research has tended to focus on disciplinary influences on data sharing, this study suggests that factors operating within the organisation have the most powerful influence on researchers' data sharing practices. The research received approval from the organisation's Human Research Ethics Committee (no. 014/18).
Claire Mason - One of the best experts on this subject based on the ideXlab platform.
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research data sharing in the australian national science agency understanding the relative importance of organisational disciplinary and Domain specific influences
PLOS ONE, 2020Co-Authors: Claire Mason, Paul Box, Shanae M BurnsAbstract:This study delineates the relative importance of organisational, research discipline and application Domain factors in influencing researchers' data sharing practices in Australia's national scientific and industrial research agency. We surveyed 354 researchers and found that the number of data deposits made by researchers were related to the openness of the data culture and the contractual inhibitors experienced by researchers. Multi-level modelling revealed that organisational unit Membership explained 10%, disciplinary Membership explained 6%, and Domain Membership explained 4% of the variance in researchers' intentions to share research data. However, only the organisational measure of openness to data sharing explained significant unique variance in data sharing. Thus, whereas previous research has tended to focus on disciplinary influences on data sharing, this study suggests that factors operating within the organisation have the most powerful influence on researchers' data sharing practices. The research received approval from the organisation's Human Research Ethics Committee (no. 014/18).
Paul Box - One of the best experts on this subject based on the ideXlab platform.
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research data sharing in the australian national science agency understanding the relative importance of organisational disciplinary and Domain specific influences
PLOS ONE, 2020Co-Authors: Claire Mason, Paul Box, Shanae M BurnsAbstract:This study delineates the relative importance of organisational, research discipline and application Domain factors in influencing researchers' data sharing practices in Australia's national scientific and industrial research agency. We surveyed 354 researchers and found that the number of data deposits made by researchers were related to the openness of the data culture and the contractual inhibitors experienced by researchers. Multi-level modelling revealed that organisational unit Membership explained 10%, disciplinary Membership explained 6%, and Domain Membership explained 4% of the variance in researchers' intentions to share research data. However, only the organisational measure of openness to data sharing explained significant unique variance in data sharing. Thus, whereas previous research has tended to focus on disciplinary influences on data sharing, this study suggests that factors operating within the organisation have the most powerful influence on researchers' data sharing practices. The research received approval from the organisation's Human Research Ethics Committee (no. 014/18).
Ricci Elisa - One of the best experts on this subject based on the ideXlab platform.
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Inferring Latent Domains for Unsupervised Deep Domain Adaptation
2019Co-Authors: Mancini Massimiliano, Porzi Lorenzo, Rota Bulò Samuel, Caputo Barbara, Ricci ElisaAbstract:Unsupervised Domain Adaptation (UDA) refers to the problem of learning a model in a target Domain where labeled data are not available by leveraging information from annotated data in a source Domain. Most deep UDA approaches operate in a single-source, single-target scenario, i.e. they assume that the source and the target samples arise from a single distribution. However, in practice most datasets can be regarded as mixtures of multiple Domains. In these cases, exploiting traditional single-source, single-target methods for learning classification models may lead to poor results. Furthermore, it is often difficult to provide the Domain labels for all data points, i.e. latent Domains should be automatically discovered. This paper introduces a novel deep architecture which addresses the problem of UDA by automatically discovering latent Domains in visual datasets and exploiting this information to learn robust target classifiers. Specifically, our architecture is based on two main components, i.e. a side branch that automatically computes the assignment of each sample to its latent Domain and novel layers that exploit Domain Membership information to appropriately align the distribution of the CNN internal feature representations to a reference distribution. We evaluate our approach on publicly available benchmarks, showing that it outperforms state-of-the-art Domain adaptation methods