Noninvasive methods for monitoring wildlife species have revolutionized the way population parameters, such as population density and survival and recruitment rates, are estimated while accounting for imperfect detection using capture-recapture models. Reliable estimates of these parameters are vital information required for making sound conservation decisions; however to date, noninvasive sampling methods have been of limited use for a vast number of species which are difficult to identify to the individual level–a general requirement of capture-recapture models. Capture-recapture models that utilize partial identity information have only recently been introduced and have not been extended to most types of noninvasive sampling scenarios in a manner that uses the spatial location where noninvasive samples were collected to further inform complete identity (i.e. spatial partial identity models). Herein, I extend the recently introduced spatial partial identity models to the noninvasive methods of remote cameras for species that are difficult to identify from photographs and DNA from hair or scat samples. The ability of these novel models to improve parameter estimation and extend study design options are investigated and the methods are made accessible to applied ecologists via statistical software. This research has the potential to greatly improve wildlife conservation decisions by improving our knowledge of parameters related to population structure and dynamics that inform those decisions. Unfortunately, many species of conservation concern (e.g., Florida panthers, Andean bears) are managed without having the necessary information on population status or trends, largely a result of the cost and difficulty of studying species in decline and because of the difficulty of applying statistical models to sparse data, which can produce imprecise and biased estimates of population parameters. By leveraging partial identity information in noninvasive samples, the models I developed will improve these parameter estimates and allow noninvasive methods to be used for more species, leading to more informed conservation decisions, and a more efficient allocation of conservation resources across species and populations. / Ph. D. / Noninvasive methods for monitoring wildlife species have revolutionized the way population parameters, such as population density and survival and recruitment rates, are estimated while accounting for imperfect detection using capture-recapture models. Reliable estimates of these parameters are vital information required for making sound conservation decisions; however to date, noninvasive sampling methods have been of limited use for a vast number of species which are difficult to identify to the individual levela general requirement of capture-recapture models. Capture-recapture models that utilize partial identity information have only recently been introduced and have not been extended to most types of noninvasive sampling scenarios in a manner that uses the spatial location where noninvasive samples were collected to further inform complete identity (i.e. spatial partial identity models). Herein, I extend the recently introduced spatial partial identity models to the noninvasive methods of remote cameras for species that are difficult to identify from photographs and DNA from hair or scat samples. The ability of these novel models to improve parameter estimation and extend study design options are investigated and the methods are made accessible to applied ecologists via statistical software. This research has the potential to greatly improve wildlife conservation decisions by improving our knowledge of parameters related to population structure and dynamics that inform those decisions. Unfortunately, many species of conservation concern (e.g., Florida panthers, Andean bears) are managed without having the necessary information on population status or trends, largely a result of the cost and difficulty of studying species in decline and because of the difficulty of applying statistical models to sparse data, which can produce imprecise and biased estimates of population parameters. By leveraging partial identity information in noninvasive samples, the models I developed will improve these parameter estimates and allow noninvasive methods to be used for more species, leading to more informed conservation decisions, and a more efficient allocation of conservation resources across species and populations.

<p>The seemingly contradictory need and want of online users for information sharing and privacy has inspired this thesis work. The crux of the problem lies in the fact that a user has inadequate control over the flow (with whom information to be shared), boundary (acceptable usage), and persistence (duration of use) of their personal information. This thesis has built a privacy-preserving information sharing model using context, identity, and trust to manage the flow, boundary, and persistence of disclosed information.</p> <p>In this vein, privacy is viewed as context-dependent selective disclosures of information. This thesis presents the design, implementation, and analysis of a five-layer Identity and Trust based Model for Privacy (ITMP). Context, trust, and identity are the main building blocks of this model. The application layer identifies the counterparts, the purpose of communication, and the information being sought. The context layer determines the context of a communication episode through identifying the role of a partner and assessing the relationship with the partner. The trust layer combines partner and purpose information with the respective context information to determine the trustworthiness of a purpose and a partner. Given that the purpose and the partner have a known level of trustworthiness, the identity layer constructs a contextual partial identity from the user's complete identity. The presentation layer facilitates in disclosing a set of information that is a subset of the respective partial identity. It also attaches expiration (time-to-live) and usage (purpose-to-live) tags into each piece of information before disclosure.</p> <p>In this model, roles and relationships are used to adequately capture the notion of context to address privacy. A role is a set of activities assigned to an actor or expected of an actor to perform. For example, an actor in a learner role is expected to be involved in various learning activities, such as attending lectures, participating in a course discussion, appearing in exams, etc. A relationship involves related entities performing activities involving one another. Interactions between actors can be heavily influenced by roles. For example, in a learning-teaching relationship, both the learner and the teacher are expected to perform their respective roles. The nuances of activities warranted by each role are dictated by individual relationships. For example, two learners seeking help from an instructor are going to present themselves differently.</p> <p>In this model, trust is realized in two forms: trust in partners and trust of purposes. The first form of trust assesses the trustworthiness of a partner in a given context. For example, a stranger may be considered untrustworthy to be given a home phone number. The second form of trust determines the relevance or justification of a purpose for seeking data in a given context. For example, seeking/providing a social insurance number for the purpose of a membership in a student organization is inappropriate. A known and tested trustee can understandably be re-trusted or re-evaluated based on the personal experience of a trustor. In online settings, however, a software manifestation of a trusted persistent public actor, namely a guarantor, is required to help find a trustee, because we interact with a myriad of actors in a large number of contexts, often with no prior relationships.</p> <p>The ITMP model is instantiated as a suite of Role- and Relationship-based Identity and Reputation Management (RRIRM) features in iHelp, an e-learning environment in use at the University of Saskatchewan. This thesis presents the results of a two-phase (pilot and larger-scale) user study that illustrates the effectiveness of the RRIRM features and thus the ITMP model in enhancing privacy through identity and trust management in the iHelp Discussion Forum. This research contributes to the understanding of privacy problems along with other competing interests in the online world, as well as to the development of privacy-enhanced communications through understanding context, negotiating identity, and using trust.</p>

<p>The seemingly contradictory need and want of online users for information sharing and privacy has inspired this thesis work. The crux of the problem lies in the fact that a user has inadequate control over the flow (with whom information to be shared), boundary (acceptable usage), and persistence (duration of use) of their personal information. This thesis has built a privacy-preserving information sharing model using context, identity, and trust to manage the flow, boundary, and persistence of disclosed information.</p> <p>In this vein, privacy is viewed as context-dependent selective disclosures of information. This thesis presents the design, implementation, and analysis of a five-layer Identity and Trust based Model for Privacy (ITMP). Context, trust, and identity are the main building blocks of this model. The application layer identifies the counterparts, the purpose of communication, and the information being sought. The context layer determines the context of a communication episode through identifying the role of a partner and assessing the relationship with the partner. The trust layer combines partner and purpose information with the respective context information to determine the trustworthiness of a purpose and a partner. Given that the purpose and the partner have a known level of trustworthiness, the identity layer constructs a contextual partial identity from the user's complete identity. The presentation layer facilitates in disclosing a set of information that is a subset of the respective partial identity. It also attaches expiration (time-to-live) and usage (purpose-to-live) tags into each piece of information before disclosure.</p> <p>In this model, roles and relationships are used to adequately capture the notion of context to address privacy. A role is a set of activities assigned to an actor or expected of an actor to perform. For example, an actor in a learner role is expected to be involved in various learning activities, such as attending lectures, participating in a course discussion, appearing in exams, etc. A relationship involves related entities performing activities involving one another. Interactions between actors can be heavily influenced by roles. For example, in a learning-teaching relationship, both the learner and the teacher are expected to perform their respective roles. The nuances of activities warranted by each role are dictated by individual relationships. For example, two learners seeking help from an instructor are going to present themselves differently.</p> <p>In this model, trust is realized in two forms: trust in partners and trust of purposes. The first form of trust assesses the trustworthiness of a partner in a given context. For example, a stranger may be considered untrustworthy to be given a home phone number. The second form of trust determines the relevance or justification of a purpose for seeking data in a given context. For example, seeking/providing a social insurance number for the purpose of a membership in a student organization is inappropriate. A known and tested trustee can understandably be re-trusted or re-evaluated based on the personal experience of a trustor. In online settings, however, a software manifestation of a trusted persistent public actor, namely a guarantor, is required to help find a trustee, because we interact with a myriad of actors in a large number of contexts, often with no prior relationships.</p> <p>The ITMP model is instantiated as a suite of Role- and Relationship-based Identity and Reputation Management (RRIRM) features in iHelp, an e-learning environment in use at the University of Saskatchewan. This thesis presents the results of a two-phase (pilot and larger-scale) user study that illustrates the effectiveness of the RRIRM features and thus the ITMP model in enhancing privacy through identity and trust management in the iHelp Discussion Forum. This research contributes to the understanding of privacy problems along with other competing interests in the online world, as well as to the development of privacy-enhanced communications through understanding context, negotiating identity, and using trust.</p>

Os sistemas Q1 e Q2, desenvolvidos por Andréa Lopari?, perfazem três principais modificações na semântica clássica: primeiramente, o universo do discurso pode não estar limitado aos objetos que pertencem ao domínio de uma dada estrutura; em segundo lugar, a relação de identidade é determinada como a diagonal desse domínio (assim, tal relação pode não ser aplicável a todas as coisas sobre as quais a linguagem possa falar); em terceiro lugar, o quantificador existencial, em Q1, bem como o universal, em Q2, podem alcançar valores que estejam fora do domínio da estrutura. Como consequência, embora definida classicamente, a negação apresenta alguns comportamentos não clássicos - a negação de um predicado numa fórmula atômica, por exemplo, pode caracterizar algo maior que, e não tão bem definido quanto, o complemento da extensão desse predicado relativamente ao domínio. [...]. / The systems Q1 and Q2, developed by Andréa Lopari?, make up three main changes in classical semantics: first, the universe of discourse can be not limited by the objects that belongs to the domain of a given structure; second, the relation of identity is fixed as a diagonal of this domain (so, it may be not applicable to all things about what the language can speak); third, the existential quantifier in Q1, as well as the universal in Q2, may capture values out of the domain of the structure. As a consequence, although classically defined, the negation presents some non-classical behavior - a negated predicate in an atomic formula, for instance, may characterize something larger and not as well defined as the complement of the extension of this predicate relatively to the domain. [...].

Os sistemas Q1 e Q2, desenvolvidos por Andréa Lopari?, perfazem três principais modificações na semântica clássica: primeiramente, o universo do discurso pode não estar limitado aos objetos que pertencem ao domínio de uma dada estrutura; em segundo lugar, a relação de identidade é determinada como a diagonal desse domínio (assim, tal relação pode não ser aplicável a todas as coisas sobre as quais a linguagem possa falar); em terceiro lugar, o quantificador existencial, em Q1, bem como o universal, em Q2, podem alcançar valores que estejam fora do domínio da estrutura. Como consequência, embora definida classicamente, a negação apresenta alguns comportamentos não clássicos - a negação de um predicado numa fórmula atômica, por exemplo, pode caracterizar algo maior que, e não tão bem definido quanto, o complemento da extensão desse predicado relativamente ao domínio. [...]. / The systems Q1 and Q2, developed by Andréa Lopari?, make up three main changes in classical semantics: first, the universe of discourse can be not limited by the objects that belongs to the domain of a given structure; second, the relation of identity is fixed as a diagonal of this domain (so, it may be not applicable to all things about what the language can speak); third, the existential quantifier in Q1, as well as the universal in Q2, may capture values out of the domain of the structure. As a consequence, although classically defined, the negation presents some non-classical behavior - a negated predicate in an atomic formula, for instance, may characterize something larger and not as well defined as the complement of the extension of this predicate relatively to the domain. [...].

Komunikace předávaná skrze Internet zahrnuje komunikaci mezi pachateli těžké trestné činnosti. Státní zástupci schvalují cílené zákonné odposlechy zaměřené na podezřelé z páchání trestné činnosti. Zákonné odposlechy se v počítačových sítích potýkají s mnoha překážkami. Identifikátory obsažené v každém paketu jsou koncovým stanicím přidělovány po omezenou dobu, nebo si je koncové stanice dokonce samy generují a automaticky mění. Tato dizertační práce se zabývá identifikačními metodami v počítačových sítích se zaměřením na metody kompatibilní se zákonnými odposlechy. Zkoumané metody musejí okamžitě detekovat použití nového identifikátoru spadajícího pod některý z odposlechů. Systém pro zákonné odposlechy následně nastaví sondy pro odposlech komunikace. Tato práce se převážně zabývá dvěma zdroji identifikačních informací: sledováním mechanismu pro objevování sousedů a detekcí identity počítače na základě přesností měření času jednotlivých počítačů. V rámci dizertačního výzkumu vznikly grafy identit, které umožňují spojování identit s ohledem na znění povolení k odposlechu. Výsledky výzkumu je možné aplikovat v rámci zákonných odposlechů, síťové forenzní analýzy i ve vysokoúrovňových programově řízených sítích.