936 resultados para Biology, Bioinformatics|Computer Science
Resumo:
The material presented in this thesis may be viewed as comprising two key parts, the first part concerns batch cryptography specifically, whilst the second deals with how this form of cryptography may be applied to security related applications such as electronic cash for improving efficiency of the protocols. The objective of batch cryptography is to devise more efficient primitive cryptographic protocols. In general, these primitives make use of some property such as homomorphism to perform a computationally expensive operation on a collective input set. The idea is to amortise an expensive operation, such as modular exponentiation, over the input. Most of the research work in this field has concentrated on its employment as a batch verifier of digital signatures. It is shown that several new attacks may be launched against these published schemes as some weaknesses are exposed. Another common use of batch cryptography is the simultaneous generation of digital signatures. There is significantly less previous work on this area, and the present schemes have some limited use in practical applications. Several new batch signatures schemes are introduced that improve upon the existing techniques and some practical uses are illustrated. Electronic cash is a technology that demands complex protocols in order to furnish several security properties. These typically include anonymity, traceability of a double spender, and off-line payment features. Presently, the most efficient schemes make use of coin divisibility to withdraw one large financial amount that may be progressively spent with one or more merchants. Several new cash schemes are introduced here that make use of batch cryptography for improving the withdrawal, payment, and deposit of electronic coins. The devised schemes apply both to the batch signature and verification techniques introduced, demonstrating improved performance over the contemporary divisible based structures. The solutions also provide an alternative paradigm for the construction of electronic cash systems. Whilst electronic cash is used as the vehicle for demonstrating the relevance of batch cryptography to security related applications, the applicability of the techniques introduced extends well beyond this.
Resumo:
Artificial neural network (ANN) learning methods provide a robust and non-linear approach to approximating the target function for many classification, regression and clustering problems. ANNs have demonstrated good predictive performance in a wide variety of practical problems. However, there are strong arguments as to why ANNs are not sufficient for the general representation of knowledge. The arguments are the poor comprehensibility of the learned ANN, and the inability to represent explanation structures. The overall objective of this thesis is to address these issues by: (1) explanation of the decision process in ANNs in the form of symbolic rules (predicate rules with variables); and (2) provision of explanatory capability by mapping the general conceptual knowledge that is learned by the neural networks into a knowledge base to be used in a rule-based reasoning system. A multi-stage methodology GYAN is developed and evaluated for the task of extracting knowledge from the trained ANNs. The extracted knowledge is represented in the form of restricted first-order logic rules, and subsequently allows user interaction by interfacing with a knowledge based reasoner. The performance of GYAN is demonstrated using a number of real world and artificial data sets. The empirical results demonstrate that: (1) an equivalent symbolic interpretation is derived describing the overall behaviour of the ANN with high accuracy and fidelity, and (2) a concise explanation is given (in terms of rules, facts and predicates activated in a reasoning episode) as to why a particular instance is being classified into a certain category.
Resumo:
Literally, the word compliance suggests conformity in fulfilling official requirements. The thesis presents the results of the analysis and design of a class of protocols called compliant cryptologic protocols (CCP). The thesis presents a notion for compliance in cryptosystems that is conducive as a cryptologic goal. CCP are employed in security systems used by at least two mutually mistrusting sets of entities. The individuals in the sets of entities only trust the design of the security system and any trusted third party the security system may include. Such a security system can be thought of as a broker between the mistrusting sets of entities. In order to provide confidence in operation for the mistrusting sets of entities, CCP must provide compliance verification mechanisms. These mechanisms are employed either by all the entities or a set of authorised entities in the system to verify the compliance of the behaviour of various participating entities with the rules of the system. It is often stated that confidentiality, integrity and authentication are the primary interests of cryptology. It is evident from the literature that authentication mechanisms employ confidentiality and integrity services to achieve their goal. Therefore, the fundamental services that any cryptographic algorithm may provide are confidentiality and integrity only. Since controlling the behaviour of the entities is not a feasible cryptologic goal,the verification of the confidentiality of any data is a futile cryptologic exercise. For example, there exists no cryptologic mechanism that would prevent an entity from willingly or unwillingly exposing its private key corresponding to a certified public key. The confidentiality of the data can only be assumed. Therefore, any verification in cryptologic protocols must take the form of integrity verification mechanisms. Thus, compliance verification must take the form of integrity verification in cryptologic protocols. A definition of compliance that is conducive as a cryptologic goal is presented as a guarantee on the confidentiality and integrity services. The definitions are employed to provide a classification mechanism for various message formats in a cryptologic protocol. The classification assists in the characterisation of protocols, which assists in providing a focus for the goals of the research. The resulting concrete goal of the research is the study of those protocols that employ message formats to provide restricted confidentiality and universal integrity services to selected data. The thesis proposes an informal technique to understand, analyse and synthesise the integrity goals of a protocol system. The thesis contains a study of key recovery,electronic cash, peer-review, electronic auction, and electronic voting protocols. All these protocols contain message format that provide restricted confidentiality and universal integrity services to selected data. The study of key recovery systems aims to achieve robust key recovery relying only on the certification procedure and without the need for tamper-resistant system modules. The result of this study is a new technique for the design of key recovery systems called hybrid key escrow. The thesis identifies a class of compliant cryptologic protocols called secure selection protocols (SSP). The uniqueness of this class of protocols is the similarity in the goals of the member protocols, namely peer-review, electronic auction and electronic voting. The problem statement describing the goals of these protocols contain a tuple,(I, D), where I usually refers to an identity of a participant and D usually refers to the data selected by the participant. SSP are interested in providing confidentiality service to the tuple for hiding the relationship between I and D, and integrity service to the tuple after its formation to prevent the modification of the tuple. The thesis provides a schema to solve the instances of SSP by employing the electronic cash technology. The thesis makes a distinction between electronic cash technology and electronic payment technology. It will treat electronic cash technology to be a certification mechanism that allows the participants to obtain a certificate on their public key, without revealing the certificate or the public key to the certifier. The thesis abstracts the certificate and the public key as the data structure called anonymous token. It proposes design schemes for the peer-review, e-auction and e-voting protocols by employing the schema with the anonymous token abstraction. The thesis concludes by providing a variety of problem statements for future research that would further enrich the literature.
Resumo:
Maintenance trains travel in convoy. In Australia, only the first train of the convoy pays attention to the track sig- nalization (the other convoy vehicles simply follow the preceding vehicle). Because of human errors, collisions can happen between the maintenance vehicles. Although an anti-collision system based on a laser distance meter is already in operation, the existing system has a limited range due to the curvature of the tracks. In this paper, we introduce an anti-collision system based on vision. The two main ideas are, (1) to warp the camera image into an image where the rails are parallel through a projective transform, and (2) to track the two rail curves simultaneously by evaluating small parallel segments. The performance of the system is demonstrated on an image dataset.
Resumo:
The topic of the present work is to study the relationship between the power of the learning algorithms on the one hand, and the expressive power of the logical language which is used to represent the problems to be learned on the other hand. The central question is whether enriching the language results in more learning power. In order to make the question relevant and nontrivial, it is required that both texts (sequences of data) and hypotheses (guesses) be translatable from the “rich” language into the “poor” one. The issue is considered for several logical languages suitable to describe structures whose domain is the set of natural numbers. It is shown that enriching the language does not give any advantage for those languages which define a monadic second-order language being decidable in the following sense: there is a fixed interpretation in the structure of natural numbers such that the set of sentences of this extended language true in that structure is decidable. But enriching the original language even by only one constant gives an advantage if this language contains a binary function symbol (which will be interpreted as addition). Furthermore, it is shown that behaviourally correct learning has exactly the same power as learning in the limit for those languages which define a monadic second-order language with the property given above, but has more power in case of languages containing a binary function symbol. Adding the natural requirement that the set of all structures to be learned is recursively enumerable, it is shown that it pays o6 to enrich the language of arithmetics for both finite learning and learning in the limit, but it does not pay off to enrich the language for behaviourally correct learning.
Resumo:
The present paper motivates the study of mind change complexity for learning minimal models of length-bounded logic programs. It establishes ordinal mind change complexity bounds for learnability of these classes both from positive facts and from positive and negative facts. Building on Angluin’s notion of finite thickness and Wright’s work on finite elasticity, Shinohara defined the property of bounded finite thickness to give a sufficient condition for learnability of indexed families of computable languages from positive data. This paper shows that an effective version of Shinohara’s notion of bounded finite thickness gives sufficient conditions for learnability with ordinal mind change bound, both in the context of learnability from positive data and for learnability from complete (both positive and negative) data. Let Omega be a notation for the first limit ordinal. Then, it is shown that if a language defining framework yields a uniformly decidable family of languages and has effective bounded finite thickness, then for each natural number m >0, the class of languages defined by formal systems of length <= m: • is identifiable in the limit from positive data with a mind change bound of Omega (power)m; • is identifiable in the limit from both positive and negative data with an ordinal mind change bound of Omega × m. The above sufficient conditions are employed to give an ordinal mind change bound for learnability of minimal models of various classes of length-bounded Prolog programs, including Shapiro’s linear programs, Arimura and Shinohara’s depth-bounded linearly covering programs, and Krishna Rao’s depth-bounded linearly moded programs. It is also noted that the bound for learning from positive data is tight for the example classes considered.