The ubiquity and speed of Internet access led over the past decade to an exponential increase in the use of thin clients and cloud computing, both taking advantage of the ability to remotely provide computing resources. The work investigates the role of remote display Protocol in behavioral biometric systems based on free-text keystroke dynamics. Authentication based on keystroke dynamics is easy in use, cheap, invisible for user and does not require any additional sensor.I n this project I will investigate how network characteristics affect the keystroke dynamics pattern in remote desktop scenario. Objectives: The aim of this project is to investigate the role of remote display Protocol in behavioral biometric system based on free-text keystroke dynamics, by measuring how network characteristics influence the computation of keystroke pattern in Virtual Desktop Infrastructure (VDI). Method: This thesis will answer all of its research question with the help of a Systematic Literature Review (SLR) and an Experiment. Literature review was conducted to gather information about the keystroke dynamics analysis, the applied algorithms and their performance; and to clarify the controlled changes of networking performance in VDI based scenario. Using the acquired knowledge, implemented keystroke dynamics pattern algorithm based on Euclidian distance statistical method, designed an experiment and performed a series of tests, in order to identify the influence of remote display protocol to keystroke pattern. Results: Through the SLR, keystroke dynamics analysis working structure is identified and illustrated, essential elements are summarized, and a statistical approach based on Euclidian distance is described; a technique to simulate and measure networklatency in VDI scenario is described including essential elements and parameters of VDI testbed. Keystroke analysis algorithm, dataset replication code and VDItestbed are implemented. The controlled experiment provided measurements of the metrics of the algorithm and network performance mentioned in objectives. Conclusions: During experimentation, I found that timing pattern in the keystroke dynamics data is affected by VDI in normal network conditions by 12% in average. Higher latency standard deviation, jitter, packet loss as well as remote display protocol overheads have a significant combined impact onto keystroke pattern. Moreover I found what maximum possible delay values does not affect keystroke pattern in a larger extent.

In the development of digitally connected solutions that require the use of personal data, the issue of data privacy is an important factor that must be taken into account. Simply informing users about how data is used and getting their consent with a simple click is not enough to create awareness of the issue of data privacy and let them make a conscious decision about the use of their personal data. Furthermore, there is a big gap in knowledge about what personal data is and what is considered sensitive data. Especially the knowledge about what biometric identifiers that they are used in a variety of everyday life applications and in which sense the handling can be problematic is unknown.This thesis project explores how the use of critical play in form of an activist game can create awareness of the issue of data privacy, inform about the value of biometric data and foster self-reflection of handling one’s own personal data. Through the simulation of dependencies between personal data, the motivation to share them and the aggregation of personal data in combination with real and prospective use cases, players are empowered to reflect on their behaviour and to critically deal with the topic of data privacy.

Bakgrund Biometriteknik är paraplybegrepp för olika automatiserade tekniker som används vid identifikation av individer. Biometriska identifikationsmetoder såsom fingeravtrycksläsning och ansiktsigenkänning har sedan länge varit reserverade för specifika syften. Idag är situationen förändrad, biometriteknik finns tillgänglig för allmänheten och används i allt större utsträckning. Biometriska metoder för identifikation kan erbjuda säkrare identifiering gentemot vanliga lösenord. Detta är av stor vikt då privatpersoner lagrar allt mer känslig information på sina mobiltelefoner, surfplattor och datorer.  Syfte   Syftet med den här studien är att undersöka hur stor inverkan faktorerna användbarhet, säkerhet och integritet har på privatpersoners användning av biometriska metoder för identifiering på mobiltelefoner, surfplattor och datorer. Efter granskning av tidigare forskning gavs dessa tre faktorer extra fokus. Den första faktorn, säkerhet, identifierades i och med att biometriteknik erbjuder förbättrad säkerhet om tekniken används korrekt. Samt att tidigare forskning pekade på säkerhet som en aspekt privatpersoner må ha i åtanke. Den andra faktorn, användbarhet, återfinns i att forskning visar på att individer värderar användbarhet och enkelhet högt. En tredje faktor, integritet, valdes i och med att viss forsking här hade nått motsägande resultat  Metod Rapporten genomfördes främst med hjälp av en kvantitativ enkätundersökning, svar (n=121) från denna undersökning användes senare för att besvara och reflektera kring forskningsfrågan: Hur stor inverkan har faktorerna användbarhet, säkerhet och integritet på privatpersoners användning av biometriteknik? Ett kapitel som namngavs forskningsöversikt inkluderas också, här har litteratur sållats kvalitativt för att finna relevanta artiklar.  Resultat Den enkätundersökning som genomfördes påvisade att en majoritet av privatpersoner använder sig av biometriska identifieringsmetoder på sina mobiltelefoner, surfplattor samt datorer. Vidare visade det sig att faktorn användbarhet värderades högt, vissa fysiologiska egenskaper som används vid biometrisk identifiering ansågs även som mer eller mindre accepterade. Svar som gavs av respondenter visade också på att privatpersoner ej resonerar speciellt mycket kring integritet och personliga data som lagras vid användning av biometriteknik.  Slutsats Efter genomförd diskussion angående tidigare forskning och de resultat som nåddes utifrån enkätundersökningen konstaterades det att faktorn användbarhet hade stor inverkan på privatpersoners användning av biometriteknik. Säkerhet tas även i åtanke av en mindre del. Faktorn integritet ges ingen eller väldigt liten uppmärksamhet gällande användning av biometriska identifieringsmetoder hos privatpersoner. / Background Biometrics is a field including different automated technologies used for thepurpose of identify individuals. Biometric identification methods such asfingerprint scanning and facial recognition used to be a field reserved forspecific application purposes. Nowadays biometrics are used more frequently,and it is available for the public to use in their everyday life. Biometrics canprovide more secure solutions compared to normal passwords, but to achievethis adoption of said methods is key, especially seeing as users store moresensitive and personal data on their smart devices compared to yesterday’s nonsmartphones. Purpose The purpose of this study is to explore how the factors usability, security andprivacy affect people’s use of biometric solutions on their smartphones,tablets, and computers. After thoroughly reviewing previous literature thesethree main factors gained extra focus. The first factor, security, biometrics dooffer greater security advantages when used the right way. Also, previousresearch points towards security as an aspect people should have in mindwhile using biometrics. The second factor, usability, this aspect is based onprevious research showing that people tend to value functions and features thatare usable. A third factor, privacy, was chosen because research showedconflicting results regarding the importance of this factor.  Method This study was conducted primarily through a quantitative survey, answers(n=121) from this survey was later used to reflect upon the research question:How much of an impact does the factors usability, security and privacy haveover peoples use of biometrics? A chapter providing an overview of previousresearch is also included, for this chapter literature has been reviewed in aqualitative matter to sort out relevant research articles.  Results Results from the survey that was conducted showed that most individuals doindeed use biometrics on their mobile phones, tablets, and computers. Datacollected also indicates that the factor usability had a big impact on peoples useof biometrics. People also responded that they saw some physiological traitsused for biometrics as more, or less accepted to be stored and collected. Otheranswers to the survey showed that individuals generally do not care too muchabout their privacy when using biometrics. Conclusion After concluded discussions regarding previous research and the resultscollected from individuals through the survey a conclusion is reached. Thefactor usability had a big impact on individuals use biometrics. A small part ofindividuals does also consider security to be important. However, the factorprivacy was mostly ignored when it comes to using biometrics on smartphones,tablets and computers.

A$ Virtual Reality (VR) becomes increasingly popular and affordable, and is applied in other fields than entertainment, such as education and industrial use, there is also a grow­ing risk related to its integrity and security. VR equipment tracks user biometric data as a means to interact with the VR environment, which creates sets of biometric data that could be used to identify u ers. Such biometric tempJates are potentially harmful if stolen by a malicious third party. This thesis investigates if user identification is possible within a set of participants ( =10) through a study using their movement and eye biometric data gathered within VR sessions, where they perform a teleoperation task designed to sim­ulate a real-world use case. By performing 3 data collection sessions for each participant and using the gathered data to train 4 classification models, we show that a high level of accuracy can be attained while using simple machine learning approaches, achieving a peak accuracy of 89.26% with a data5et designed to challenge our models. We further ana­lyze the accuracy results from the trained models, and di5cuss the identification power of different data types, which highlights how the characteristics of the task performed affects the usefulness of data types.

This paper investigates the growing concerns surrounding the utilisation of biometric technology within humanitarian organisations, with a specific focus on the Biometric Information Management System (BIMS) operated by UNHCR. The study is based on a literature review in which themes of concern are first identified in theoretical literature followed by an examination of empirical literature (here termed ‘refugee-including literature’) to see if the concerns are shared. The primary aim is to offer a comprehensive understanding of biometric concerns by amalgamating previous research, while at the same time bringing to light the specific concerns voiced directly by refugees themselves. Using Michel Foucault’s biopolitics and Michael Barnett’s humanitarian governance, the findings reveal two overarching themes shared between the theoretical and refugee-including literature: Concerns of Power (agency, data-access, and the testing of new technologies) and Concerns of Policy (function creep, fraud prevention, and technosolutionism). The study also finds that refugee-including literature presents an additional concern not seen in the theoretical literature: limitations on economic agency, while excluding another: concerns about private company data-access. The refugee-including literature is also found to offer some remarks in support of biometric registration. In conclusion, this study not only sheds light on concerns surrounding humanitarian biometrics, it also highlights the distinctive insights provided by refugees themselves. The paper concludes with a set of recommendations aimed at addressing the identified concerns and promoting responsible and ethical use of biometric technology in humanitarian operations.

Security is becoming an increasingly important issue for business, and with it comes the need for appropriate authentication; consequently, it is becoming gradually more important to develop secure e-commerce systems. Fraud via the web, identity theft, and phishing are raising concerns for users and financial organisations. In addition, current authentication methods, like passwords, have many problems (e.g. some users write them down, they forget them, or they make them easy to hack). We can overcome these drawbacks by using biometric authentication systems. Biometric systems are being used for personal authentication in response to the rising issue of authentication and security. Biometrics provide much promise, in terms of preserving our identities without the inconvenience of carrying ID cards and/or remembering passwords. This research is important because the securing of e-commerce transactions is becoming increasingly important. Identity theft, hacking and viruses are growing threats to Internet users. As more people use the Internet, more identity theft cases are being reported. This could harm not only the users, but also the reputation of the organisations whose names are used in these illegal acts. For example, in the UK, online banking fraud doubled in 2008 compared to 2007. More users took to e-shopping and online banking, but failed to take necessary protection. For non-western cultures, the figures for web security, in 2008, illustrated that Saudi Arabia was ranked ninth worldwide for users who had been attacked over the web. The above statistics reflect the significance of information security with e-commerce systems. As with any new technology, user acceptance of the new technology is often hard to measure. In this thesis, a study of user acceptance of biometric authentication systems in e-transactions, such as online banking, within Saudi society was conducted. It examined whether Saudis are practically willing to accept this technology. This thesis focuses upon Saudi Arabia, which has developing economy. It has achieved a rapid rate of growth, and therefore makes an interesting and unique case study. From an economist¿s point of view, Saudi Arabia is the powerhouse of the Middle East. It has the leading regional economy, and, even though it is still relatively young. It has a young and rapid growing population; therefore, this makes Saudi Arabia an attractive potential market for all kinds of e-commerce applications. Having said that, with more than half of population under the age of 30 are more to be expected to take the risk of accepting new technology. For this work, 306 Saudi participants were involved in the experiments. A laboratory experiment was created that actively tested a biometric authentication system in combination with a survey. The Technology Acceptance Model (TAM) was adopted in the first experimental phase as the theoretical basis on which to develop the iv research framework, the model has proven its efficiency as a good predictor for the biometric authentication system. Furthermore, in a second experimental phase, the Unified Theory of Acceptance and Use of Technology (UTAUT) with moderating variables such as age, gender and education level was examined as a proposed conceptual framework to overcome the limitations of TAM. The aim of the study was to explore factors affecting users¿ acceptance of biometric authentication systems. The findings from Structural Equation Modelling (SEM) analysis indicate that education level is a significant moderating factor, while gender and age do not record as significant. This thesis added new knowledge to this field and highlighted the importance of the perceptions of users regarding biometric security technologies. It helps determine the factors affecting the acceptance of biometric technology. To our knowledge, this is the first systematic study of this issue carried out by academic and non-biased researchers in Saudi Arabia. Furthermore, the thesis presents security technology companies and developers of information security products with information to help in the determination of what is significant to their user base when taking into account the introduction of new secure systems and products.

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We live in an era of advanced technological innovations and it is therefore difficult to acquire a proper overview of the different surveillance techniques deployed for the purpose of enhancing and administrating migration control. The intent of this paper is to disseminate one of the new technologies on the market: the biometric technology that is an identification and verification system based on measurements of biological traits. Different approaches are used to explore and investigate the technological functions, social structures and political justifications for their validity and their role in the implementation of the biometric technology. The paper also provides an overview of the different areas of political and social management that are affected by the implementation of the biometric techniques.The principal aim of this work is to examine how the implementation of the biometric techniques will affect privacy for all people, taking both information privacy and personal integrity into consideration. The second question deals with migration management, as the current implementation mainly involves travel documents. It focuses on the consequences of the so-called war on terror and its call for prevention of terrorism and irregular migration. The dilemma between national security and the right to privacy, public good and private interests, and the realms of state and individual rights are also discussed and analysed.Hence, the framework and the fundamental structure of this thesis are based on three core issues pertinent to the implementation of biometrics in the EU: threats posed on the right to privacy, securitization of migration, and intensification of surveillance and state control. The findings are used to identify the threats posed on right to privacy and the way this right is compromised, and the consequences of practices and policies in the field of migration that are discriminatory and exclusory. Lastly, by employing different theories, this paper examines why state seeks technological control over citizens and why individuals comply with state control and surveillance.

With the rapid development of computers andmodels for machine learning, image recognition has, in recentyears, become widespread in various areas. In this report, imagerecognition is discussed in relation to biometric identificationusing fingerprint images. The aim is to investigate how well abiometric identification model can be trained with an extendeddataset, which resulted from rotating and shifting the images inthe original dataset consisting of very few images. Furthermore,it is investigated how the accuracy of this single-stage modeldiffers from the accuracy of a model with two-stage identification.We chose Random Forest (RF) as the machine learning modeland Scikit default values for the hyperparameters. We furtherincluded five-fold cross-validation in the training process. Theperformance of the trained machine learning model is evaluatedwith testing accuracy and confusion matrices. It was shown thatthe method for extending the dataset was successful. A greaternumber of images gave a greater accuracy in the predictions.Two-stage identification gave approximately the same accuracyas the single-stage method, but both methods would need tobe tested on datasets with images from a greater number ofindividuals before any final conclusions can be drawn. / Tack vare den snabba utvecklingen av datoreroch modeller för maskininlärning har bildigenkänning desenaste åren fått stor spridning i samhället. I denna rapportbehandlas bildigenkänning i relation till biometrisk identifieringi form av fingeravtrycksavläsning. Målet är att undersöka hurväl en modell för biometrisk identifiering kan tränas och testaspå ett dataset med ursprungligen mycket få bilder, om datasettetförst expanderas genom att flertalet kopior av originalbildernaskapas och sedan roteras och förskjuts i olika riktningar.Vidare undersöks hur noggrannheten för denna enstegsmodellskiljer sig jämfört med identifiering i två steg. Vi valdeRandom Forest (RF) som maskininlärningsmodell och Scikitsstandardinställningar för hyperparametrarna. Vidare inkluderadesfemfaldig korsvalidering i träningsprocessen. Prestandanhos den tränade maskininlärningsmodellen bedömdes med hjälpav testnoggrannhet och confusion matriser. Det visades sig attmetoden för att expandera datasettet var framgångsrik. Ettstörre antal bilder gav större noggrannhet i förutsägelserna.Tvåstegsidentifiering gav ungefärligen samma noggrannhet somenstegsidentifiering, men metoderna skulle behöva testas på datamängder med bilder från ett större antal individer innannågra slutgiltiga slutsatser kan dras. / Kandidatexjobb i elektroteknik 2021, KTH, Stockholm

Biometrics includes the study of automatic methods for distinguishing human beings based on physical or behavioral traits. The problem of finding good biometric features and recognition methods has been researched extensively in recent years. Our research considers the use of ears as a biometric for human recognition. Researchers have not considered this biometric as much as others, which include fingerprints, irises, and faces. This thesis presents a novel approach to recognize individuals based on their outer ear images through spatial segmentation. This approach to recognizing is also good for dealing with occlusions. The study will present several feature extraction techniques based on spatial segmentation of the ear image. The study will also present a method for classifier fusion. Principal components analysis (PCA) is used in this research for feature extraction and dimensionality reduction. For classification, nearest neighbor classifiers are used. The research also investigates the use of ear images as a supplement to face images in a multimodal biometric system. Our base eigen-ear experiment results in an 84% rank one recognition rate, and the segmentation method yielded improvements up to 94%. Face recognition by itself, using the same approach, gave a 63% rank one recognition rate, but when complimented with ear images in a multimodal system improved to 94% rank one recognition rate. / Master of Science