In this thesis I discuss the problems associated with the epistemological task of arriving at basic logical knowledge. This is knowledge that the primitive rules of inference we use in deductive reasoning are correct. Knowledge of correctness, like all knowledge, is available to us either as the product of inference, or it is available non-inferentially. Success in the campaign to justify the correctness of these rules is mired by opposing views on how to do this properly. Inferential justifications of rules of inference, which are based on reasons, lead to regressive or circular results. Non-inferential justifications, based on something other than reasons, at first do not seem to fare any better: without a basis for these justifications, they appear arbitrary and unfounded. The works of Boghossian and Dummett who argue for an inferentialist approach, and Hale who supports non-inferentialism are carefully examined in this thesis. I conclude by finding superiority in Hale's suggestion that a particular set of basic logical constants are indispensable to deductive reasoning. I suggest that we endorse a principle which states that rules are not premises, and are therefore to be excluded from expression as statements in a deductive argument. I argue that the quality of being indispensable is sufficient for a basic rule of deduction to be countenanced as default-justified, and therefore need not be expressed in argument. By a rule's evading expression in argument, it avoids circular reasoning in deductive arguments about its own correctness. Another important outcome that emerges from my research is the finding that non-inferential knowledge is ontologically prior to the inferential sort. This is because plausible inferential knowledge of basic logical constants shall always be justified by circular reasoning that already assumes the correctness of the rule to be vindicated. This initial assumption is tantamount to non-inferential knowledge, and therefore this latter is more primitive-in fact the only primitive-species of basic logical knowledge.

In this thesis I discuss the problems associated with the epistemological task of arriving at basic logical knowledge. This is knowledge that the primitive rules of inference we use in deductive reasoning are correct. Knowledge of correctness, like all knowledge, is available to us either as the product of inference, or it is available non-inferentially. Success in the campaign to justify the correctness of these rules is mired by opposing views on how to do this properly. Inferential justifications of rules of inference, which are based on reasons, lead to regressive or circular results. Non-inferential justifications, based on something other than reasons, at first do not seem to fare any better: without a basis for these justifications, they appear arbitrary and unfounded. The works of Boghossian and Dummett who argue for an inferentialist approach, and Hale who supports non-inferentialism are carefully examined in this thesis. I conclude by finding superiority in Hale's suggestion that a particular set of basic logical constants are indispensable to deductive reasoning. I suggest that we endorse a principle which states that rules are not premises, and are therefore to be excluded from expression as statements in a deductive argument. I argue that the quality of being indispensable is sufficient for a basic rule of deduction to be countenanced as default-justified, and therefore need not be expressed in argument. By a rule's evading expression in argument, it avoids circular reasoning in deductive arguments about its own correctness. Another important outcome that emerges from my research is the finding that non-inferential knowledge is ontologically prior to the inferential sort. This is because plausible inferential knowledge of basic logical constants shall always be justified by circular reasoning that already assumes the correctness of the rule to be vindicated. This initial assumption is tantamount to non-inferential knowledge, and therefore this latter is more primitive-in fact the only primitive-species of basic logical knowledge.

With the rapid development of information technology, data availability is improved greatly. Data may be accessed at anytime by people from any location. However,threats to data security and privacy arise as one of the major problems of the development of information systems, especially those information systems which contain personal information. An association database is a personal information system which contains associations between persons. In this thesis, we identify the security and privacy problems of association databases. In order to solve these problems, we propose a new security and privacy model for association databases equipped with both direct access control and inference control mechanisms. In this model, there are multiple criteria including, not only confidentiality, but also privacy and other aspects of security to classify the association. The methods used in the system are: The direct access control method is based on the mandatory model; The inference control method is based on both logic reasoning and probabilistic reasoning (Belief Networks). My contributions to security and privacy model for association databases and to inference control in the model include: Identification of security and privacy problems in association databases; Formal definition of association database model; Representation association databases as directed multiple graphs; Development of axioms for direct access control; Specification of the unauthorized inference problem; A method for unauthorized inference detection and control that includes: Development of logic inference rules and probabilistic inference rule; Application of belief networks as a tool for unauthorized inference detection and control.

With the rapid development of information technology, data availability is improved greatly. Data may be accessed at anytime by people from any location. However,threats to data security and privacy arise as one of the major problems of the development of information systems, especially those information systems which contain personal information. An association database is a personal information system which contains associations between persons. In this thesis, we identify the security and privacy problems of association databases. In order to solve these problems, we propose a new security and privacy model for association databases equipped with both direct access control and inference control mechanisms. In this model, there are multiple criteria including, not only confidentiality, but also privacy and other aspects of security to classify the association. The methods used in the system are: The direct access control method is based on the mandatory model; The inference control method is based on both logic reasoning and probabilistic reasoning (Belief Networks). My contributions to security and privacy model for association databases and to inference control in the model include: Identification of security and privacy problems in association databases; Formal definition of association database model; Representation association databases as directed multiple graphs; Development of axioms for direct access control; Specification of the unauthorized inference problem; A method for unauthorized inference detection and control that includes: Development of logic inference rules and probabilistic inference rule; Application of belief networks as a tool for unauthorized inference detection and control.