902 resultados para fuzzy vault, multiple biometrics, biometric cryptosystem, biometrics and cryptography
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Collaboration in the public sector is imperative to achieve e-government objectives such as improved efficiency and effectiveness of public administration and improved quality of public services. Collaboration across organizational and institutional boundaries requires public organizations to share e-government systems and services through for instance, interoperable information technology and processes. Demands on public organizations to become more open also require that public organizations adopt new collaborative approaches for inviting and engaging citizens in governmental activities. E-government related collaboration in the public sector is challenging, however, and collaboration initiatives often fail. Public organizations need to learn how to collaborate since forms of e-government collaboration and expected outcomes are mostly unknown. How public organizations can collaborate and the expected outcomes are thus investigated in this thesis by studying multiple collaboration cases on the acquisition and implementation of a particular e-government investment (digital archive). This thesis also investigates how e-government collaboration can be facilitated through artifacts. It is done through a case study, where objects that cross boundaries between collaborating communities in the public sector are studied, and by designing a configurable process model integrating several processes for social services. By using design science, this thesis also investigates how an m-government solution that facilitates collaboration between citizens and public organizations can be designed. The thesis contributes to literature through describing five different modes of interorganizational collaboration in the public sector and the expected benefits from each mode. It also contributes with an instantiation of a configurable process model supporting three open social e-services and with evidence of how it can facilitate collaboration. This thesis further describes how boundary objects facilitate collaboration between different communities in an open government design initiative. It contributes with a designed mobile government solution, thereby providing proof of concept and initial design implications for enabling collaboration with citizens through citizen sourcing (outsourcing a governmental activity to citizens through an open call). This thesis also identifies research streams within e-government collaboration research through a literature review and the thesis contributions are related to the identified research streams. This thesis gives directions for future research by suggesting that future research should focus further on understanding e-government collaboration and how information and communication technology can facilitate collaboration in the public sector. It is suggested that further research should investigate m-government solutions to form design theories. Future research should also examine how value can be co-created in e-government collaboration.
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Multiple endocrine neoplasia syndromes have since been classified as types 1 and 2, each with specific phenotypic patterns. MEN1 is usually associated with pituitary, parathyroid and paraneoplastic neuroendocrine tumours. The hallmark of MEN2 is a very high lifetime risk of developing medullary thyroid carcinoma (MTC) more than 95% in untreated patients. Three clinical subtypesdMEN2A, MEN2B, and familial MTC (FMTC) have been defined based on the risk of pheochromocytoma, hyperparathyroidism, and the presence or absence of characteristic physical features). MEN2 occurs as a result of germline activating missense mutations of the RET (REarranged during Transfection) proto-oncogene. MEN2-associated mutations are almost always located in exons 10, 11, or 13 through 16. Strong genotype-phenotype correlations exist with respect to clinical subtype, age at onset, and aggressiveness of MTC in MEN2. These are used to determine the age at which prophylactic thyroidectomy should occur and whether screening for pheochromocytoma or hyperparathyroidism is necessary. Specific RET mutations can also impact management in patients presenting with apparently sporadic MTC. Therefore, genetic testing should be performed before surgical intervention in all patients diagnosed with MTC. Recently, Pellegata et al. have reported that germline mutations in CDKN1B can predispose to the development of multiple endocrine tumours in both rats and humans and this new MEN syndrome is named MENX and MEN4, respectively. CDKN1B. A recent report showed that in sporadic MTC, CDKN1B V109G polymorphism correlates with a more favorable disease progression than the wild-type allele and might be considered a new promising prognostic marker. New insights on MEN syndrome pathogenesis and related inherited endocrine disorders are of particular interest for an adequate surgical and therapeutic approach.
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The goal of image retrieval and matching is to find and locate object instances in images from a large-scale image database. While visual features are abundant, how to combine them to improve performance by individual features remains a challenging task. In this work, we focus on leveraging multiple features for accurate and efficient image retrieval and matching. We first propose two graph-based approaches to rerank initially retrieved images for generic image retrieval. In the graph, vertices are images while edges are similarities between image pairs. Our first approach employs a mixture Markov model based on a random walk model on multiple graphs to fuse graphs. We introduce a probabilistic model to compute the importance of each feature for graph fusion under a naive Bayesian formulation, which requires statistics of similarities from a manually labeled dataset containing irrelevant images. To reduce human labeling, we further propose a fully unsupervised reranking algorithm based on a submodular objective function that can be efficiently optimized by greedy algorithm. By maximizing an information gain term over the graph, our submodular function favors a subset of database images that are similar to query images and resemble each other. The function also exploits the rank relationships of images from multiple ranked lists obtained by different features. We then study a more well-defined application, person re-identification, where the database contains labeled images of human bodies captured by multiple cameras. Re-identifications from multiple cameras are regarded as related tasks to exploit shared information. We apply a novel multi-task learning algorithm using both low level features and attributes. A low rank attribute embedding is joint learned within the multi-task learning formulation to embed original binary attributes to a continuous attribute space, where incorrect and incomplete attributes are rectified and recovered. To locate objects in images, we design an object detector based on object proposals and deep convolutional neural networks (CNN) in view of the emergence of deep networks. We improve a Fast RCNN framework and investigate two new strategies to detect objects accurately and efficiently: scale-dependent pooling (SDP) and cascaded rejection classifiers (CRC). The SDP improves detection accuracy by exploiting appropriate convolutional features depending on the scale of input object proposals. The CRC effectively utilizes convolutional features and greatly eliminates negative proposals in a cascaded manner, while maintaining a high recall for true objects. The two strategies together improve the detection accuracy and reduce the computational cost.
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The study evaluated the effects of herbivory pressure, nutrient availability and potential propagule supply on recruitment and succession of coral reef macroalgal communities. Recruitment and succession tiles were placed in a nutrient-herbivory factorial experiment and macroalgal abundances were evaluated through time. Proportional abundances of macroalgal form-functional groups on recruitment and succession tiles were similar to field established communities within treatments, evidencing possible effects of adult macroalgae as propagule supply. Macroalgal abundance of recruitment tiles increased with nutrient loading and herbivory reduction combined whereas on succession tiles nutrient loading increased abundance of articulated-calcareous only when herbivores were excluded. Macroalgal field established communities were only affected by herbivory reduction.
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The rapid development of data transfer through internet made it easier to send the data accurate and faster to the destination. There are many transmission media to transfer the data to destination like e-mails; at the same time it is may be easier to modify and misuse the valuable information through hacking. So, in order to transfer the data securely to the destination without any modifications, there are many approaches like cryptography and steganography. This paper deals with the image steganography as well as with the different security issues, general overview of cryptography, steganography and digital watermarking approaches. The problem of copyright violation of multimedia data has increased due to the enormous growth of computer networks that provides fast and error free transmission of any unauthorized duplicate and possibly manipulated copy of multimedia information. In order to be effective for copyright protection, digital watermark must be robust which are difficult to remove from the object in which they are embedded despite a variety of possible attacks. The message to be send safe and secure, we use watermarking. We use invisible watermarking to embed the message using LSB (Least Significant Bit) steganographic technique. The standard LSB technique embed the message in every pixel, but my contribution for this proposed watermarking, works with the hint for embedding the message only on the image edges alone. If the hacker knows that the system uses LSB technique also, it cannot decrypt correct message. To make my system robust and secure, we added cryptography algorithm as Vigenere square. Whereas the message is transmitted in cipher text and its added advantage to the proposed system. The standard Vigenere square algorithm works with either lower case or upper case. The proposed cryptography algorithm is Vigenere square with extension of numbers also. We can keep the crypto key with combination of characters and numbers. So by using these modifications and updating in this existing algorithm and combination of cryptography and steganography method we develop a secure and strong watermarking method. Performance of this watermarking scheme has been analyzed by evaluating the robustness of the algorithm with PSNR (Peak Signal to Noise Ratio) and MSE (Mean Square Error) against the quality of the image for large amount of data. While coming to see results of the proposed encryption, higher value of 89dB of PSNR with small value of MSE is 0.0017. Then it seems the proposed watermarking system is secure and robust for hiding secure information in any digital system, because this system collect the properties of both steganography and cryptography sciences.
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Who was the cowboy in Washington? What is the land of sushi? Most people would have answers to these questions readily available,yet, modern search engines, arguably the epitome of technology in finding answers to most questions, are completely unable to do so. It seems that people capture few information items to rapidly converge to a seemingly 'obvious' solution. We will study approaches for this problem, with two additional hard demands that constrain the space of possible theories: the sought model must be both psychologically and neuroscienti cally plausible. Building on top of the mathematical model of memory called Sparse Distributed Memory, we will see how some well-known methods in cryptography can point toward a promising, comprehensive, solution that preserves four crucial properties of human psychology.
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Genetic decoding is not ‘frozen’ as was earlier thought, but dynamic. One facet of this is frameshifting that often results in synthesis of a C-terminal region encoded by a new frame. Ribosomal frameshifting is utilized for the synthesis of additional products, for regulatory purposes and for translational ‘correction’ of problem or ‘savior’ indels. Utilization for synthesis of additional products occurs prominently in the decoding of mobile chromosomal element and viral genomes. One class of regulatory frameshifting of stable chromosomal genes governs cellular polyamine levels from yeasts to humans. In many cases of productively utilized frameshifting, the proportion of ribosomes that frameshift at a shift-prone site is enhanced by specific nascent peptide or mRNA context features. Such mRNA signals, which can be 5′ or 3′ of the shift site or both, can act by pairing with ribosomal RNA or as stem loops or pseudoknots even with one component being 4 kb 3′ from the shift site. Transcriptional realignment at slippage-prone sequences also generates productively utilized products encoded trans-frame with respect to the genomic sequence. This too can be enhanced by nucleic acid structure. Together with dynamic codon redefinition, frameshifting is one of the forms of recoding that enriches gene expression.
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Automated border control (ABC) is concerned with fast and secure processing for intelligence-led identification. The FastPass project aims to build a harmonised, modular reference system for future European ABC. When biometrics is taken on board as identity, spoofing attacks become a concern. This paper presents current research in algorithm development for counter-spoofing attacks in biometrics. Focussing on three biometric traits, face, fingerprint, and iris, it examines possible types of spoofing attacks, and reviews existing algorithms reported in relevant academic papers in the area of countering measures to biometric spoofing attacks. It indicates that the new developing trend is fusion of multiple biometrics against spoofing attacks.
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The ever increasing spurt in digital crimes such as image manipulation, image tampering, signature forgery, image forgery, illegal transaction, etc. have hard pressed the demand to combat these forms of criminal activities. In this direction, biometrics - the computer-based validation of a persons' identity is becoming more and more essential particularly for high security systems. The essence of biometrics is the measurement of person’s physiological or behavioral characteristics, it enables authentication of a person’s identity. Biometric-based authentication is also becoming increasingly important in computer-based applications because the amount of sensitive data stored in such systems is growing. The new demands of biometric systems are robustness, high recognition rates, capability to handle imprecision, uncertainties of non-statistical kind and magnanimous flexibility. It is exactly here that, the role of soft computing techniques comes to play. The main aim of this write-up is to present a pragmatic view on applications of soft computing techniques in biometrics and to analyze its impact. It is found that soft computing has already made inroads in terms of individual methods or in combination. Applications of varieties of neural networks top the list followed by fuzzy logic and evolutionary algorithms. In a nutshell, the soft computing paradigms are used for biometric tasks such as feature extraction, dimensionality reduction, pattern identification, pattern mapping and the like.
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Cryptographic systems are safe. However, the management of cryptographic keys of these systems is a tough task. They are usually protected by the use of password-based authentication mechanisms, which is a weak link on conventional cryptographic systems, as the passwords can be easily copied or stolen. The usage of a biometric approach for releasing the keys is an alternative to the password-based mechanisms. But just like passwords, we need mechanisms to keep the biometrical signal safe. One approach for such mechanism is to use biometrical key cryptography. The cryptographic systems based on the use of biometric characteristics as keys are called biometrical cryptographic systems. This article presents the implementation of Fuzzy Vault, a biometrical cryptographic system written in Java, along with its performance evaluation. Fuzzy Vault was tested on a real application using smartcards.
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Until recently the use of biometrics was restricted to high-security environments and criminal identification applications, for economic and technological reasons. However, in recent years, biometric authentication has become part of daily lives of people. The large scale use of biometrics has shown that users within the system may have different degrees of accuracy. Some people may have trouble authenticating, while others may be particularly vulnerable to imitation. Recent studies have investigated and identified these types of users, giving them the names of animals: Sheep, Goats, Lambs, Wolves, Doves, Chameleons, Worms and Phantoms. The aim of this study is to evaluate the existence of these users types in a database of fingerprints and propose a new way of investigating them, based on the performance of verification between subjects samples. Once introduced some basic concepts in biometrics and fingerprint, we present the biometric menagerie and how to evaluate them.
Resumo:
Until recently the use of biometrics was restricted to high-security environments and criminal identification applications, for economic and technological reasons. However, in recent years, biometric authentication has become part of daily lives of people. The large scale use of biometrics has shown that users within the system may have different degrees of accuracy. Some people may have trouble authenticating, while others may be particularly vulnerable to imitation. Recent studies have investigated and identified these types of users, giving them the names of animals: Sheep, Goats, Lambs, Wolves, Doves, Chameleons, Worms and Phantoms. The aim of this study is to evaluate the existence of these users types in a database of fingerprints and propose a new way of investigating them, based on the performance of verification between subjects samples. Once introduced some basic concepts in biometrics and fingerprint, we present the biometric menagerie and how to evaluate them.
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In the last years there was an exponential growth in the offering of Web-enabled distance courses and in the number of enrolments in corporate and higher education using this modality. However, the lack of efficient mechanisms that assures user authentication in this sort of environment, in the system login as well as throughout his session, has been pointed out as a serious deficiency. Some studies have been led about possible biometric applications for web authentication. However, password based authentication still prevails. With the popularization of biometric enabled devices and resultant fall of prices for the collection of biometric traits, biometrics is reconsidered as a secure remote authentication form for web applications. In this work, the face recognition accuracy, captured on-line by a webcam in Internet environment, is investigated, simulating the natural interaction of a person in the context of a distance course environment. Partial results show that this technique can be successfully applied to confirm the presence of users throughout the course attendance in an educational distance course. An efficient client/server architecture is also proposed. © 2009 Springer Berlin Heidelberg.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)