Enhancement in iris recognition system using FPGA

The growth of using the iris recognition over the globe for identification and for verification and the problem that faces the iris recognition from noise like eyelash and eyelid. This paper focus on choosing the right pattern to collect the traits. The algorithm of this paper is searching and working on different rectangle iris template to spotting the ultimate traits that lies within rectangle iris templates. The Ridge Energy Direction (RED) is used as algorithm to spot the features that lies within the template. The overall iris system is design, implemented and tested on the Field Programmable gate Area (FPGA)

Privacy protecting biometric authentication systems

As biometrics gains popularity and proliferates into the daily life, there is an increased concern over the loss of privacy and potential misuse of biometric data held in central repositories. The major concerns are about i) the use of biometrics to track people, ii) non-revocability of biometrics (eg. if a fingerprint is compromised it can not be canceled or reissued), and iii) disclosure of sensitive information such as race, gender and health problems which may be revealed by biometric traits. The straightforward suggestion of keeping the biometric data in a user owned token (eg. smart cards) does not completely solve the problem, since malicious users can claim that their token is broken to avoid biometric verification altogether. Put together, these concerns brought the need for privacy preserving biometric authentication methods in the recent years. In this dissertation, we survey existing privacy preserving biometric systems and implement and analyze fuzzy vault in particular; we propose a new privacy preserving approach; and we study the discriminative capability of online signatures as it relates to the success of using online signatures in the available privacy preserving biometric verification systems. Our privacy preserving authentication scheme combines multiple biometric traits to obtain a multi-biometric template that hides the constituent biometrics and allows the possibility of creating non-unique identifiers for a person, such that linking separate template databases is impossible. We provide two separate realizations of the framework: one uses two separate fingerprints of the same individual to obtain a combined biometric template, while the other one combines a fingerprint with a vocal pass-phrase. We show that both realizations of the framework are successful in verifying a person's identity given both biometric traits, while preserving privacy (i.e. biometric data is protected and the combined identifier can not be used to track people). The Fuzzy Vault emerged as a promising construct which can be used in protecting biometric templates. It combines biometrics and cryptography in order to get the benefits of both fields; while biometrics provides non-repudiation and convenience, cryptography guarantees privacy and adjustable levels of security. On the other hand, the fuzzy vault is a general construct for unordered data, and as such, it is not straightforward how it can be used with different biometric traits. In the scope of this thesis, we demonstrate realizations of the fuzzy vault using fingerprints and online signatures such that authentication can be done while biometric templates are protected. We then demonstrate how to use the fuzzy vault for secret sharing, using biometrics. Secret sharing schemes are cryptographic constructs where a secret is split into shares and distributed amongst the participants in such a way that it is constructed/revealed only when a necessary number of share holders come together (e.g. in joint bank accounts). The revealed secret can then be used for encryption or authentication. Finally, we implemented how correlation attacks can be used to unlock the vault; showing that further measures are needed to protect the fuzzy vault against such attacks. The discriminative capability of a biometric modality is based on its uniqueness/entropy and is an important factor in choosing a biometric for a large-scale deployment or a cryptographic application. We present an individuality model for online signatures in order to substantiate their applicability in biometric authentication. In order to build our model, we adopt the Fourier domain representation of the signature and propose a matching algorithm. The signature individuality is measured as the probability of a coincidental match between two arbitrary signatures, where model parameters are estimated using a large signature database. Based on this preliminary model and estimated parameters, we conclude that an average online signature provides a high level of security for authentication purposes. Finally, we provide a public online signature database along with associated testing protocols that can be used for testing signature verification system

Securing Cloud Storage by Transparent Biometric Cryptography

With the capability of storing huge volumes of data over the Internet, cloud storage has become a popular and desirable service for individuals and enterprises. The security issues, nevertheless, have been the intense debate within the cloud community. Significant attacks can be taken place, the most common being guessing the (poor) passwords. Given weaknesses with verification credentials, malicious attacks have happened across a variety of well-known storage services (i.e. Dropbox and Google Drive) – resulting in loss the privacy and confidentiality of files. Whilst today's use of third-party cryptographic applications can independently encrypt data, it arguably places a significant burden upon the user in terms of manually ciphering/deciphering each file and administering numerous keys in addition to the login password. The field of biometric cryptography applies biometric modalities within cryptography to produce robust bio-crypto keys without having to remember them. There are, nonetheless, still specific flaws associated with the security of the established bio-crypto key and its usability. Users currently should present their biometric modalities intrusively each time a file needs to be encrypted/decrypted – thus leading to cumbersomeness and inconvenience while throughout usage. Transparent biometrics seeks to eliminate the explicit interaction for verification and thereby remove the user inconvenience. However, the application of transparent biometric within bio-cryptography can increase the variability of the biometric sample leading to further challenges on reproducing the bio-crypto key. An innovative bio-cryptographic approach is developed to non-intrusively encrypt/decrypt data by a bio-crypto key established from transparent biometrics on the fly without storing it somewhere using a backpropagation neural network. This approach seeks to handle the shortcomings of the password login, and concurrently removes the usability issues of the third-party cryptographic applications – thus enabling a more secure and usable user-oriented level of encryption to reinforce the security controls within cloud-based storage. The challenge represents the ability of the innovative bio-cryptographic approach to generate a reproducible bio-crypto key by selective transparent biometric modalities including fingerprint, face and keystrokes which are inherently noisier than their traditional counterparts. Accordingly, sets of experiments using functional and practical datasets reflecting a transparent and unconstrained sample collection are conducted to determine the reliability of creating a non-intrusive and repeatable bio-crypto key of a 256-bit length. With numerous samples being acquired in a non-intrusive fashion, the system would be spontaneously able to capture 6 samples within minute window of time. There is a possibility then to trade-off the false rejection against the false acceptance to tackle the high error, as long as the correct key can be generated via at least one successful sample. As such, the experiments demonstrate that a correct key can be generated to the genuine user once a minute and the average FAR was 0.9%, 0.06%, and 0.06% for fingerprint, face, and keystrokes respectively. For further reinforcing the effectiveness of the key generation approach, other sets of experiments are also implemented to determine what impact the multibiometric approach would have upon the performance at the feature phase versus the matching phase. Holistically, the multibiometric key generation approach demonstrates the superiority in generating the bio-crypto key of a 256-bit in comparison with the single biometric approach. In particular, the feature-level fusion outperforms the matching-level fusion at producing the valid correct key with limited illegitimacy attempts in compromising it – 0.02% FAR rate overall. Accordingly, the thesis proposes an innovative bio-cryptosystem architecture by which cloud-independent encryption is provided to protect the users' personal data in a more reliable and usable fashion using non-intrusive multimodal biometrics.Higher Committee of Education Development in Iraq (HCED

MINDFUL INQUIRY - A DEWEYAN ASSESSMENT OF MINDFULNESS AND EDUCATION

Mindfulness-based interventions are becoming an increasingly popular means for helpingstudents deal with the multidimensional challenges they face in contemporary educational settings. While potentially helpful, an uncritical employment of mindfulness in education can paradoxically function to reify the very neoliberal social conditions leading to the need for mindfulness in the first place. I assess this trend in educational theory and practice through John Dewey’s pragmatic philosophy. I show that the potential for both mindfulness and Dewey’s theory of mind and inquiry to support critical, sustainable social change is truncated by an uncritical retaining of the modern paradigm of mind that defines mind and cognition as private mental events internal to individual subjects. Following Dewey, I critique this view of mind as dubious according to the ontological assumptions underlying this paradigm. By presenting an original reading of Dewey’s theory of mind, life, and inquiry based on an autopoietic process ontology and the life-mind continuity thesis, I show that the sciences of mind are currently in the midst of a revolutionary period of science, shifting from a paradigm rooted in the substance metaphysical tradition to a new, transdisciplinary paradigm animated by process metaphysics and radically different theories of mind, life, and cognition, heuristically captured by the life- mind continuity thesis. On this view, life and mind are of a piece; where there is life there is mind. Showing that Dewey developed one of the first and most complete theories of this thesis, I integrate Dewey’s theories of mind and inquiry with the contemporary mindfulness movement and discuss how they can work together to enable a critical, socially engaged yet compassionate and uniqueness-respecting framework for a somatic-based holistic social inquiry in education. I call this mindful inquiry

Government Data Mining: The Need for a Legal Framework

The article examines the government\u27s growing appetite for collecting personal data. Often justified on the basis of protecting national security, government data mining programs sweep up data collected through hundreds of regulatory and administrative programs, and combine them with huge datasets obtained from industry. The result is an aggregation of personal data - the digital footprints of individual lives - never before seen. These data warehouses are then used to determine who can work and participate in Social Security programs, who can board airplanes and enter government buildings, and who is likely to pose a threat in the future, even though they have done nothing wrong to date. The article describes the extraordinary volume and variety of personal data to which the government has routine access, directly and through industry, and examines the absence of any meaningful limits on that access. So-called privacy statutes are often so outdated and inadequate that they fail to limit the government\u27s access to our most personal data, or they have been amended in the post-9/11 world to reduce those limits. And the Fourth Amendment, the primary constitutional guarantee of individual privacy, has been interpreted by the Supreme Court to not apply to routine data collection, accessing data from third parties, or sharing data, even if illegally gathered. The result is not only that individual privacy goes unprotected, but that national security is compromised because it is increasingly based on data mining initiatives that are untested, ill focused, and rely on inaccurate or incomplete data. These shortcomings, and the urgent need for Congress to act to address them, have been widely recognized by numerous public and private commissions, but largely ignored by members of Congress - republicans and democrats alike. The article concludes that there is wide agreement about both the need to restore some limits on the government\u27s use of personal data and the form that those limits should take. The problem is the unwillingness - or inability - of Congress to act

Virtual Reality Games for Motor Rehabilitation

This paper presents a fuzzy logic based method to track user satisfaction without the need for devices to monitor users physiological conditions. User satisfaction is the key to any product’s acceptance; computer applications and video games provide a unique opportunity to provide a tailored environment for each user to better suit their needs. We have implemented a non-adaptive fuzzy logic model of emotion, based on the emotional component of the Fuzzy Logic Adaptive Model of Emotion (FLAME) proposed by El-Nasr, to estimate player emotion in UnrealTournament 2004. In this paper we describe the implementation of this system and present the results of one of several play tests. Our research contradicts the current literature that suggests physiological measurements are needed. We show that it is possible to use a software only method to estimate user emotion

The presentation of self in Massively Multiplayer Online games

This thesis examined the presentation of self in Massively Multiplayer Online games, to investigate how players create and maintain versions of self in these environments. Key research questions concerned the motivation for engaging in these behaviours, the impact of such activities on their offline lives and for those that did not engage in the active presentation of self, why they did not do this. There were three studies in the thesis, employing a combination of qualitative and quantitative methods. The first study consisted of interviews (n=29), analysed using Grounded theory, and the second an online focus group (n=13 participants) explored using thematic analysis. These results were combined to create a theoretical model for the presentation of self in MMOs. Based on these concept statements a third study (n=408) was created, using an online questionnaire design. Results indicated that a five factor model was the most satisfactory means of explaining the presentation of self in MMOs – with Presentation of the Existing Self, Social Interaction, Gaming Aesthetics, Presenting Different Sides of the Self, and Emotional Impact as the salient factors

Controversing Datafication through Media Architectures

In this chapter, we discuss a speculative and participatory “media architecture” installation that engages people with the potential impacts of data through speculative future images of the datafied city. The installation was originally conceived as a physical combination of digital media technologies and architectural form—a “media architecture”—that was to be situated in a particular urban setting. Due to the COVID-19 pandemic, however, it was produced and tested for an online workshop. It is centered on “design frictions” (Forlano and Mathew, 2014) and processes of controversing (Baibarac-Duignan and de Lange, 2021). Instead of smoothing out tensions through “neutral” data visualizations, controversing centers on opening avenues for meaningful participation around frictions and controversies that arise from the datafication of urban life. The installation represents an instance of how processes of controversing may unfold through digital interfaces. Here, we explore its performative potential to “interface” abstract dimensions of datafication, “translate” them into collective issues of concern, and spark imagination around (un)desirable datafied urban futures