In the present study, I look at the relationship between power and identity verification and the conditions under which this relationship can be disrupted. Specifically, I look at the role of information in disrupting power differences within identity processes. I examine these processes through an experiment with task-oriented, power-imbalanced, dyads (N=144). Priming participants with a task-leader identity, I test how the introduction of negotiation resources—or information discrepant and external to a high power actor’s self presentation, affect presentation power—or the degree to which an actor can maintain identity meanings in light of partner negotiations. In contrast with existing literature, I did not find a direct relationship between power and identity verification. I did, however, find that those in higher positions of power experience greater identity stability, while those in lower positions of power experience increased identity change. Interestingly, I found that identity change and identity verification varied with identity valence, such that those with dominant task leader identity meanings experienced greater identity stability but less identity verification than their more submissive counterparts. These relationships, however were power dependent, such that differences disappeared among power-high actors, and were magnified for power-low actors. Negotiation Resources did not have a significant main effect, but showed a significant interaction with identity valence when predicting identity verification among power-low actors.

<p>In the age of a networking revolution, when the Internet has changed not only the way we see computing, but also the whole society, we constantly face new challenges in the area of user verification. It is often the case that the login-id password pair does not provide a sufficient level of security. Other, more sophisticated techniques are used: one-time passwords, smart cards or biometric identity verification. The biometric approach is considered to be one of the most secure ways of authentication. </p><p>On the other hand, many biometric methods require additional hardware in order to sample the corresponding biometric feature, which increases the costs and the complexity of implementation. There is however one biometric technique which does not demand any additional hardware – user identification based on keyboard statistics. This thesis is focused on this way of authentication. </p><p>The keyboard statistics approach is based on the user’s unique typing rhythm. Not only what the user types, but also how she/he types is important. This report describes the statistical analysis of typing samples which were collected from 20 volunteers, as well as the implementation and testing of the identity verification system, which uses the characteristics examined in the experimental stage.</p>

In the age of a networking revolution, when the Internet has changed not only the way we see computing, but also the whole society, we constantly face new challenges in the area of user verification. It is often the case that the login-id password pair does not provide a sufficient level of security. Other, more sophisticated techniques are used: one-time passwords, smart cards or biometric identity verification. The biometric approach is considered to be one of the most secure ways of authentication. On the other hand, many biometric methods require additional hardware in order to sample the corresponding biometric feature, which increases the costs and the complexity of implementation. There is however one biometric technique which does not demand any additional hardware – user identification based on keyboard statistics. This thesis is focused on this way of authentication. The keyboard statistics approach is based on the user’s unique typing rhythm. Not only what the user types, but also how she/he types is important. This report describes the statistical analysis of typing samples which were collected from 20 volunteers, as well as the implementation and testing of the identity verification system, which uses the characteristics examined in the experimental stage.

With the advancement in multimedia systems and the increased interest in haptics to be used in interpersonal communication systems, where users can see, show, hear, tell, touch and be touched, mouse and keyboard are no longer dominant input devices. Touch, speech and vision will soon be the main methods of human computer interaction. Moreover, as interpersonal communication usage increases, the need for securing user authentication grows. In this research, we examine a user's identification and verification based on haptic information. We divide our research into three main steps. The first step is to examine a pre-defined task, namely a handwritten signature with haptic information. The user target in this task is to mimic the legitimate signature in order to be verified. As a second step, we consider the user's identification and verification based on user drawings. The user target is predefined, however there are no restrictions imposed on the order or on the level of details required for the drawing. Lastly, we examine the feasibility and possibility of distinguishing users based on their haptic interaction through an interpersonal communication system. In this third step, there are no restrictions on user movements, however a free movement to touch the remote party is expected. In order to achieve our goal, many classification and feature reduction techniques have been discovered and some new ones were proposed. Moreover, in this work we utilize evolutionary computing in user verification and identification. Analysis of haptic features and their significance on distinguishing users is hence examined. The results show a utilization of visual features by Genetic Programming (GP) towards identity verification, with a probability equal to 50% while the remaining haptic features were utilized with a probability of approximately 50%. Moreover, with a handwritten signature application, a verification success rate of 97.93% with False Acceptance Rate (FAR) of 1.28% and @11.54% False Rejection Rate (FRR) is achieved with the utilization of genetic programming enhanced with the random over sampled data set. In addition, with a totally free user movement in a haptic-enabled interpersonal communication system, an identification success rate of 83.3% is achieved when random forest classifier is utilized.

Interest in facial recognition has increased rapidly during the past decade. Increased computational power and huge amounts of available data have made facial recognition both possible and useful. Bio-metrical identification is one of the common applications for facial recognition.The population in Sweden is aging. Moreover, many people remain living on their own until old age. This introduces new challenges to society. How do we maintain the autonomy of elderly, and support their well-being despite of the challenges introduced by aging?This thesis presents a study of the potential of facial recognition in elderly care. In the thesis work a need for facial recognition system in elderly care is identified, a system architecture to meet the need is presented, the implementation process of such system’s prototype is described, and the feasibility of the prototype is evaluated.One of the results of the study indicates that there is a need in elderly care to help seniors to verify and identify caregivers who visit them. The study shows that a facial recognition system which presents information about the visiting caregiver to the elderly would support them in their daily life. The user interface of the developed prototype is feasible, but as it is now, the facial recognition part of the program is not accurate enough to be used in a real life context. Ways of improving the facial recognition functionality of such a system should be studied in future research. / Intresset för ansiktsigenkänning har ökat snabbt under det senaste decenniet. Detta har gjort ansiktsigenkänning både möjlig och användbar. Biometri och identifiering är vanliga användningssätt för ansiktsigenkänning.Sverige befolkning åldras. De äldre fortsätter dessutom att i hög grad bo ensamma. Detta introducerar nya utmaningar för samhället. Hur kan vi bibehålla de äldres autonomi and stötta deras välmående, trots ålderns krämpor?Denna uppsats presenterar en studie om potentialen för att använda ansiktsigenkänning inom äldrevården. I arbetet identifieras behovet av ett ansiktsigenkänningssystem inom äldrevården, en systemarkitektur för att tillgodose detta behov presenteras, implementeringsprocessen av en prototyp av ett sådant system beskrivs samt genomförbarheten av ett sådant system utvärderas. Ett av studiens resultat indikerar att det finns ett behov inom äldreomsorgen att hjälpa seniorer att identifiera och verifiera den personal som besöker dem. Studien visar att ett ansiktsigenkänningssystem som visar information om besökande personal till seniorerna skulle kunna hjälpa dem i deras dagliga liv.Användargränssnittet i den utvecklade prototypen är användbar, men i dess nuvarande stadie är ansiktsigenkänningsdelen av programmet inte exakt nog för att kunna användas i verkligheten. Metoder för att förbättra ansiktsigenkänningsfunktionen i ett sådant system är ett uppslag för framtida forskning.

A procedure is presented that is capable of extracting various speaker features, and is of particular value for analyzing records containing single words and shorter segments of speech. By taking advantage of the fast convergence properties of adaptive filtering, the approach is capable of modeling the nonstationarities due to both the vocal tract and vocal cord dynamics. Specifically, the procedure extracts the vocal tract estimate from within the closed glottis interval and uses it to obtain a time-domain glottal signal. This procedure is quite simple, requires minimal manual intervention (in cases of inadequate pitch detection), and is particularly unique because it derives both the vocal tract and glottal signal estimates directly from the time-varying filter coefficients rather than from the prediction error signal. Using this procedure, several glottal signals are derived from human and synthesized speech and are analyzed to demonstrate the glottal waveform modeling performance and kind of glottal characteristics obtained therewith. Finally, the procedure is evaluated using automatic speaker identity verification. / Ph. D.

Identity verification is ubiquitous in our daily life. By verifying the user's identity, the authorization process grants the privilege to access resources or facilities or perform certain tasks. The traditional and most prevalent authentication method is the personal identification number (PIN) or password. While these knowledge-based credentials could be lost or stolen, human biometric-based verification technologies have become popular alternatives in recent years. Nowadays, more people are used to unlocking their smartphones using their fingerprint or face instead of the conventional passcode. However, these biometric approaches have their weaknesses. For example, fingerprints could be easily fabricated, and a photo or image could spoof the face recognition system. In addition, these existing biometric-based identity verification methods could continue if the user is unaware, sleeping, or even unconscious. Therefore, an additional level of security is needed. In this dissertation, we demonstrate a novel identity verification approach, which makes the biometric authentication process more secure. Our approach requires only one regular camera to acquire a short video for computing the face and facial motion representations. It takes advantage of the advancements in computer vision and deep learning techniques. Our new deep neural network model, or facial motion encoder, can generate a representation vector for the facial motion in the video. Then the decision algorithm compares the vector to the enrolled facial motion vector to determine their similarity for identity verification. We first proved its feasibility through a keypoint-based method. After that, we built a curated dataset and proposed a novel representation learning framework for facial motions. The experimental results show that this facial motion verification approach reaches an average precision of 98.8\%, which is more than adequate for customary use. We also tested this algorithm on complex facial motions and proposed a new self-supervised pretraining approach to boost the encoder's performance. At last, we evaluated two other potential upstream tasks that could help improve the efficiency of facial motion encoding. Through these efforts, we have built a solid benchmark for facial motion representation learning, and the elaborate techniques can inspire other face analysis and video understanding research.

This thesis is an investigation into the unique rural banking system in Ghana and the role of information systems in fraud control. It presents a robust information security and internal control model to deal with fraud for the banking system. The rural banking industry has been noted for poor internal control leading to fraud. This has resulted in poor performance and even the collapse of some banks. The Focus of the study was on the processes used to deliver banking services. To design a protection system, a number of rural banks were visited. This was to understand the environment, regulatory regimes and the structure and banking processes of the industry and banks. Systemic vulnerabilities within the industry which could be exploited for fraud were found. The lack of structures like an address system and unreliable identification documents makes it difficult to use conventional identification processes. Also the lack of adequate controls, small staff numbers and the cross organisational nature of some transactions among other cultural issues reduces the ability to implement transaction controls. Twenty fraud scenarios were derived to illustrate the manifestation of these vulnerabilities. The rural banking integrity model was developed to deal with these observations. This protection model was developed using existing information security models and banking control mechanisms but incorporating the nature of the rural banking industry and culture of its environment. The fraud protection model was tested against the fraud scenarios and was shown to meet the needs of the rural banking industry in dealing with its systemic vulnerabilities. The proposed community-based identification scheme deals with identification weaknesses as an alternative to conventional identity verification mechanisms. The Transaction Authentication Code uses traditional adinkra symbols. Whilst other mechanisms like the Transaction Verification Code design v internal controls into the banking processes. This deals with various process control weaknesses and avoids human discretion in complying with controls. Object based separation of duties is also introduced as a means of controlling conflicting tasks which could lead to fraud.

This thesis is an investigation into the unique rural banking system in Ghana and the role of information systems in fraud control. It presents a robust information security and internal control model to deal with fraud for the banking system. The rural banking industry has been noted for poor internal control leading to fraud. This has resulted in poor performance and even the collapse of some banks. The Focus of the study was on the processes used to deliver banking services. To design a protection system, a number of rural banks were visited. This was to understand the environment, regulatory regimes and the structure and banking processes of the industry and banks. Systemic vulnerabilities within the industry which could be exploited for fraud were found. The lack of structures like an address system and unreliable identification documents makes it difficult to use conventional identification processes. Also the lack of adequate controls, small staff numbers and the cross organisational nature of some transactions among other cultural issues reduces the ability to implement transaction controls. Twenty fraud scenarios were derived to illustrate the manifestation of these vulnerabilities. The rural banking integrity model was developed to deal with these observations. This protection model was developed using existing information security models and banking control mechanisms but incorporating the nature of the rural banking industry and culture of its environment. The fraud protection model was tested against the fraud scenarios and was shown to meet the needs of the rural banking industry in dealing with its systemic vulnerabilities. The proposed community-based identification scheme deals with identification weaknesses as an alternative to conventional identity verification mechanisms. The Transaction Authentication Code uses traditional adinkra symbols. Whilst other mechanisms like the Transaction Verification Code design v internal controls into the banking processes. This deals with various process control weaknesses and avoids human discretion in complying with controls. Object based separation of duties is also introduced as a means of controlling conflicting tasks which could lead to fraud.

Dans cette thèse, nous avons adapté trois versions d'une chaine d'algorithmes de reconnaissance biométrique par l’iris appelés OSIRIS V2, V3, V4 qui correspondent à différentes implémentations de l’approche de J. Daugman pour les besoins d’une implémentation logicielle / matérielle. Les résultats expérimentaux sur la base de données ICE2005 montrent que OSIRIS_V4 est le système le plus fiable alors qu’OSIRIS_V2 est le plus rapide. Nous avons proposé une mesure de qualité de l’image segmentée pour optimiser en terme de compromis coût / performance un système de référence basé sur OSIRIS V2 et V4. Nous nous sommes ensuite intéressés à l’implémentation de ces algorithmes sur des plateformes reconfigurables. Les résultats expérimentaux montrent que l’implémentation matériel / logiciel est plus rapide que l’implémentation purement logicielle. Nous proposons aussi une nouvelle méthode pour le partitionnement matériel / logiciel de l’application. Nous avons utilisé la programmation linéaire pour trouver la partition optimale pour les différentes tâches prenant en compte les trois contraintes : la surface occupée, le temps d’exécution et la consommation d’énergie / In this thesis, we adapted three versions of a chain of algorithms for biometric iris recognition called OSIRIS V2, V3, V4, which correspond to different implementations of J. Daugman approach. The experimental results on the database ICE2005 show that OSIRIS_V4 is the most reliable when OSIRIS_V2 is the fastest. We proposed a measure of quality of the segmented image in order to optimize in terms of cost / performance compromise a reference system based on OSIRIS V2 and V4. We focused on the implementation of these algorithms on reconfigurable platforms. The experimental results show that the hardware / software implementation is faster than the software implementation. We propose a new method for partitioning hardware / software application. We used linear programming to find the optimal partition for different tasks taking into account the three constraints : the occupied area, execution time and energy consumption